Job Summary : Were looking for a results-driven Web/Data Analyst to join our analytics team, supporting data-led decisions across digital campaigns and player experience optimization. While experience in the gaming/betting industry is a plus, its not a prerequisite. The ideal candidate is passionate about using data to uncover insights, improve user engagement, and drive measurable outcomes through structured testing and performance reporting. Key Responsibilities : - Conduct in-depth analysis of A/B testing experiments, interpreting data to evaluate performance and derive actionable insights. - Translate web analytics and user engagement data into actionable insights and concise reports. - Prepare and deliver regular updates and dashboards on campaign performance metrics. - Work cross-functionally with game designers, marketers, and product teams to influence testing strategies and performance improvements. - Work with web analytics tools (e.g., Google Analytics, Adobe Analytics) to track user behaviour and performance KPIs. - Utilize web and in-game analytics tools to track KPIs such as retention, conversion, engagement, and monetization. - Translate complex data into clear, concise reports for both technical and non-technical stakeholders. Required Skills : - Proficiency in web analytics platforms (Google Analytics, Adobe Analytics, etc.) - Strong skills in Excel, SQL, and data visualization tools (Tableau, Power BI, or similar). - Solid understanding of A/B testing frameworks and digital marketing metrics. - Excellent analytical and problem-solving skills with attention to detail. - Strong communication skills to clearly present findings and recommendations. Preferred Qualifications : - Bachelors degree with 3+ years of experience. - Experience with tag management and tracking tools is a plus (e.g., GTM)

Hyderabad

Saras Analytics - Web/Data Analyst - Tableau/Power BI (3-5 yrs)

We are seeking a highly skilled and motivated AI/ML Engineer to join our team. The ideal candidate will have extensive experience in developing, deploying, and optimizing machine learning models and pipelines. You will be responsible for automating workflows, transitioning proofs of concept (POCs) into production environments, and building scalable solutions such as customer segmentation, demand forecasting, and market mix models. Additionally, you will work with cutting-edge AI advancements, including Retrieval-Augmented Generation (RAG) and AI Agents, contributing to end-to-end automated Data Science solutions. Key Responsibilities : - Design, develop, and implement machine learning pipelines for automated workflows and customer insights generation. - Build and optimize predictive models for applications such as demand forecasting, inventory forecasting, and market mix modelling. - Develop natural language processing (NLP) modules leveraging techniques such as Retrieval-Augmented Generation (RAG) and AI Agents with LLMs. - Deploy machine learning models into production environments, ensuring scalability, reliability, and efficiency. - Transition POCs from experimentation to fully operational, production-grade systems. - Collaborate with cross-functional teams, including data scientists, engineers, and stakeholders, to translate business needs into ML solutions. - Apply containerization tools (e., Docker) and orchestration platforms (e., Kubernetes) for efficient deployment and lifecycle management of ML models. - Monitor, evaluate, and refine machine learning models to maintain performance and accuracy. - Stay updated on advancements in AI, machine learning, and data science technologies. Required Qualifications : - Bachelors or Masters degree in Computer Science, Machine Learning, Data Science, or a related field. - Proven experience in machine learning engineering or a similar role. - Proficiency in Python and its data science libraries. - Hands-on experience with ML frameworks such as PyTorch and TensorFlow. - Strong knowledge of data pre-processing, feature engineering, and model evaluation methodologies. - Understanding of NLP concepts, including pre-processing, embeddings, entity recognition, and vector storage. - Experience with containerization (Docker) and orchestration tools (Kubernetes). - Demonstrated ability to transition POCs into scalable production solutions. - Experience developing models for demand forecasting, inventory forecasting, or marketing analytics. - Familiarity with cloud platforms such as GCP and Azure, and their machine learning services. - Understanding of LLM architectures, statistical modelling, and advanced analytics techniques. - Proven ability to build, debug, and optimize large, high-performance ML training jobs. - Excellent problem-solving skills and a collaborative mindset. Preferred Skills : - Experience with CI/CD pipelines for ML model integration and deployment. - Familiarity with MLOps tools and practices. - Strong communication skills to explain technical concepts to non-technical stakeholders. What We Offer : - Competitive salary and comprehensive benefits package. - Opportunities to work on innovative and impactful AI projects. - A collaborative and inclusive work environment. - Continuous learning and professional development opportunities

Saras Analytics - Artificial Intelligence/Machine Learning Engineer - RAG/LLM (3-5 yrs)

About Saras Analytics : We are an ecommerce focused end to end data analytics firm assisting enterprises & brands in data driven decision making to maximize business value. Our suite of work spans extraction, transformation, visualization & analysis of data delivered via industry leading products, solutions & services. Our flagship product is Daton, an ETL tool. We have now ventured into building exciting ease of use data visualization solutions on top of Daton. And lastly, we have a world class data team which understands the story the numbers are telling and articulates the same to CXOs thereby creating value. Where we are Today : We are a boot strapped, profitable & fast growing (2x y-o-y) startup with old school value systems. We play in a very exciting space which is intersection of data analytics & ecommerce both of which are game changers. Today, the global economy faces headwinds forcing companies to downsize, outsource & offshore creating strong tail winds for us. We are an employee first company valuing talent & encouraging talent and live by those values at all stages of our work without comprising on the value we create for our customers. We strive to make Saras a career and not a job for talented folks who have chosen to work with us. The Role : We are seeking an accomplished Lead Data Engineer with strong programming skills, cloud expertise, and in-depth knowledge of Big Query/Snowflake data warehousing technologies. As a key leader in our data engineering team, you will play a critical role in designing, implementing, and optimizing data pipelines, leveraging your expertise in programming, cloud platforms, and modern data warehousing solutions. Responsibilities : Data Pipeline Architecture : - Lead the design and architecture of scalable and efficient data pipelines, ensuring optimal performance and reliability. Programming and Scripting : - Utilize strong programming skills, particularly in languages like Python, for developing robust and maintainable data engineering solutions. Cloud Platform Expertise : - Apply extensive experience with cloud platforms (e.g., AWS, Azure, Google Cloud) to design, deploy, and optimize data engineering solutions in a cloud environment. BigQuery/Snowflake Knowledge : - Demonstrate deep understanding and hands-on experience with BigQuery/Snowflake for efficient data storage, processing, and analysis. ETL Processes : - Lead the development of Extract, Transform, Load (ETL) processes, ensuring seamless integration of data from various sources into the data warehouse. Data Modeling and Optimization : - Design and implement effective data models to support ETL processes and ensure data integrity and efficiency. Collaboration and Leadership : - Collaborate with cross-functional teams, providing technical leadership and guidance to junior data engineers. - Work closely with data scientists, analysts, and business stakeholders to understand requirements and deliver effective data solutions. Quality Assurance : - Implement comprehensive data quality checks and validation processes to ensure the accuracy and completeness of data. Documentation : - Create and maintain detailed documentation for data engineering processes, data models, and cloud configurations. Technical Skills : - Programming Languages : Expertise in programming languages, with a strong emphasis on Python. - Cloud Platforms : Extensive experience with cloud platforms such as AWS, Azure, or Google Cloud. - Big Data Technologies : Proficiency in big data technologies and frameworks for distributed computing. - Data Warehousing : In-depth knowledge of modern data warehousing solutions, with specific expertise in BigQuery/Snowflake. - ETL Tools : Experience with ETL tools like Apache NiFi, Talend, or similar. - SQL : Strong proficiency in writing and optimizing SQL queries for data extraction, transformation, and loading. - Collaboration Tools : Experience using collaboration and project management tools for effective communication and project tracking. Soft Skills : - Strong leadership and mentoring capabilities. - Excellent communication and presentation skills. - Strategic thinking and problem-solving abilities. - Ability to work collaboratively in a cross-functional team environment. Educational Qualifications : - Bachelors or Masters degree in Computer Science Data Engineering, or a related field. Experience : - 8+ years of experience in data engineering roles with a focus on programming, cloud platforms, and data warehousing. - If you are an experienced Lead Data Engineer with a strong programming background, cloud expertise, and specific knowledge of BigQuery/Snowflake, we encourage you to apply.

Saras Analytics - Lead Data Engineer - BigQuery/Snowflake DB (8-12 yrs)

Technical Requirements (Mandatory) : - 5+ years of experience in relevant job roles - Excellent Communication skills and analytical skills - Excellent data interpretation skills, with proven track record deriving actionable business insights from large data sets - Proficiency in client communication and stakeholder management - Advanced general aptitude, problem solving and critical thinking ability - Experience creating executive presentations in PowerPoint - Experience performing cost-benefit analyses and creating proposals. - Working knowledge of SDLC lifecycle and collaborating with product teams. Understanding of : Data Manipulation tools - SQL and Excel - Visualization tools - At least one of PowerBI, Tableau, DataStudio/Looker - Cloud databases - BigQuery, Snowflake, Redshift or Azure - Working knowledge of Agile practices and sprint management in tools like JIRA or Asana. Behavioural Expectations (Mandatory) : Individual traits essential to be successful in this role : - Self-motivation to work with abstract guidance. - Proactiveness to add business value. - Empathy to deal with multiple external and internal stakeholders. - Adaptability to work in cross-functional and high-performing teams. - Prioritization to visualize the big picture and maximize impact of outputs. - Perform RCAs and identify new data driven opportunities for adding business value or improving process productivity. - Communicate effectively about delivery: requirements, timelines, dependencies, priorities, etc. ensuring timely delivery without compromising on quality standards. - Act as an SME by leading trainings for business stakeholders and mentoring juniors as needed. Other Requirements (Preferred) : - Bachelor's or master's degree in relevant fields like MBA, Computer Science Engineering, Finance, Statistics from reputed academic institutions - 2+ years of experience working in eCommerce or digitally native organizations. - Conceptual understanding of eCommerce/Omnichannel tools and platforms - Sales Channels - Shopify, Amazon, Walmart - Marketing - Customer Purchase Cycle - Analytics - Google Analytics Benefits : - Competitive salary and performance-based bonuses. - Comprehensive health insurance, relocation benefits and other allowances - Professional development opportunities and continued learning - A collaborative and innovative work environment

Saras Analytics - Senior Business Analyst - eCommerce Platform (5-7 yrs)

Key Responsibilities : - Develop and optimize data pipelines (ETL) and cloud tools (AWS/Azure/GCP). - Design efficient data models and architecture for cloud data warehouses. - Collaborate with data scientists and other teams. - Implement data quality checks and validation processes to ensure the accuracy and completeness of data in the cloud-based data warehouse. - Collaborate with cross-functional teams to identify and address data quality issues. - Monitor and troubleshoot issues, ensuring timely resolution and minimal impact on data availability. Required Skills : - Proficiency for data engineering, scripting, and automation. - Hands-on experience with AWS, Azure, or Google Cloud (specific services like BigQuery, Redshift, Synapse, Dataflow, Glue). - Experience with distributed processing (Spark) and workflow management (Airflow). - Strong proficiency in SQL and designing effective data models. - Proven expertise in implementing ETL. - Strong problem-solving, communication, and collaboration

Telangana

Saras Analytics - Data Engineer/Senior Engineer - ETL (3-5 yrs)

About Saras Analytics : We are an ecommerce focused end to end data analytics firm assisting enterprises & brands in data driven decision making to maximize business value. Our suite of work spans extraction, transformation, visualization & analysis of data delivered via industry leading products, solutions & services. Our flagship product is Daton, an ETL tool. We have now ventured into building exciting ease of use data visualization solutions on top of Daton. And lastly, we have a world class data team which understands the story the numbers are telling and articulates the same to CXOs thereby creating value.Where we are Today : We are a boot strapped, profitable & fast growing (2x y-o-y) startup with old school value systems. We play in a very exciting space which is intersection of data analytics & ecommerce both of which are game changers. Today, the global economy faces headwinds forcing companies to downsize, outsource & offshore creating strong tail winds for us. We are an employee first company valuing talent & encouraging talent and live by those values at all stages of our work without comprising on the value we create for our customers. We strive to make Saras a career and not a job for talented folks who have chosen to work with us.The Role : We are seeking an accomplished Lead Data Engineer with strong programming skills, cloud expertise, and in-depth knowledge of Big Query/Snowflake data warehousing technologies. As a key leader in our data engineering team, you will play a critical role in designing, implementing, and optimizing data pipelines, leveraging your expertise in programming, cloud platforms, and modern data warehousing solutions.Responsibilities : Data Pipeline Architecture : - Lead the design and architecture of scalable and efficient data pipelines, ensuring optimal performance and reliability. Programming and Scripting : - Utilize strong programming skills, particularly in languages like Python, for developing robust and maintainable data engineering solutions. Cloud Platform Expertise : - Apply extensive experience with cloud platforms (e.g., AWS, Azure, Google Cloud) to design, deploy, and optimize data engineering solutions in a cloud environment. BigQuery/Snowflake Knowledge : - Demonstrate deep understanding and hands-on experience with BigQuery/Snowflake for efficient data storage, processing, and analysis. ETL Processes : - Lead the development of Extract, Transform, Load (ETL) processes, ensuring seamless integration of data from various sources into the data warehouse. Data Modeling and Optimization : - Design and implement effective data models to support ETL processes and ensure data integrity and efficiency. Collaboration and Leadership : - Collaborate with cross-functional teams, providing technical leadership and guidance to junior data engineers. - Work closely with data scientists, analysts, and business stakeholders to understand requirements and deliver effective data solutions. Quality Assurance : - Implement comprehensive data quality checks and validation processes to ensure the accuracy and completeness of data. Documentation : - Create and maintain detailed documentation for data engineering processes, data models, and cloud configurations.Technical Skills : Programming Languages : Expertise in programming languages, with a strong emphasis on Python. Cloud Platforms : Extensive experience with cloud platforms such as AWS, Azure, or Google Cloud. Big Data Technologies : Proficiency in big data technologies and frameworks for distributed computing. Data Warehousing : In-depth knowledge of modern data warehousing solutions, with specific expertise in BigQuery/Snowflake. ETL Tools : Experience with ETL tools like Apache NiFi, Talend, or similar. SQL : Strong proficiency in writing and optimizing SQL queries for data extraction, transformation, and loading. Collaboration Tools : Experience using collaboration and project management tools for effective communication and project tracking.Soft Skills : - Strong leadership and mentoring capabilities. - Excellent communication and presentation skills. - Strategic thinking and problem-solving abilities. - Ability to work collaboratively in a cross-functional team environment. Educational Qualifications : Bachelors or Masters degree in Computer Science Data Engineering, or a related field. Experience : - 8+ years of experience in data engineering roles with a focus on programming, cloud platforms, and data warehousing. - If you are an experienced Lead Data Engineer with a strong programming background, cloud expertise, and specific knowledge of BigQuery/Snowflake, we encourage you to apply.

Saras Analytics - Lead Data Engineer - Python (8-10 yrs)

About Saras Analytics : We are an ecommerce focused end to end data analytics firm assisting enterprises & brands in data driven decision making to maximize business value. Our suite of work spans extraction, transformation, visualization & analysis of data delivered via industry leading products, solutions & services. Our flagship product is Daton, an ETL tool. We have now ventured into building exciting ease of use data visualization solutions on top of Daton. And lastly, we have a world class data team which understands the story the numbers are telling and articulates the same to CXOs thereby creating value. Where we are Today : We are a boot strapped, profitable & fast growing (2x y-o-y) startup with old school value systems. We play in a very exciting space which is intersection of data analytics & ecommerce both of which are game changers. Today, the global economy faces headwinds forcing companies to downsize, outsource & offshore creating strong tail winds for us. We are an employee first company valuing talent & encouraging talent and live by those values at all stages of our work without comprising on the value we create for our customers. We strive to make Saras a career and not a job for talented folks who have chosen to work with us. The Role : We are seeking a seasoned and proficient Senior Python Data Engineer with substantial experience in cloud technologies. As a pivotal member of our data engineering team, you will play a crucial role in designing, implementing, and optimizing data pipelines, ensuring seamless integration with cloud platforms. The ideal candidate will possess a strong command of Python, data engineering principles, and a proven track record of successful implementation of scalable solutions in cloud environments. Responsibilities : Data Pipeline Development : - Design, develop, and maintain scalable and efficient data pipelines using Python and cloud-based technologies. - Implement Extract, Transform, Load (ETL) processes to seamlessly move data from diverse sources into our cloud-based data warehouse. Cloud Integration : - Utilize cloud platforms (e.g., Google Cloud, AWS, Azure) to deploy, manage, and optimize data engineering solutions. - Leverage cloud-native services for storage, processing, and analysis of large datasets. Data Modelling and Architecture : - Collaborate with data scientists, analysts, and other stakeholders to design effective data models that align with business requirements. - Ensure the scalability, reliability, and performance of the overall data infrastructure on cloud platforms. Optimization and Performance : - Continuously optimize data processes for improved performance, scalability, and cost-effectiveness in a cloud environment. - Monitor and troubleshoot issues, ensuring timely resolution and minimal impact on data availability. Quality Assurance : - Implement data quality checks and validation processes to ensure the accuracy and completeness of data in the cloud-based data warehouse. - Collaborate with cross-functional teams to identify and address data quality issues. Collaboration and Communication : - Work closely with data scientists, analysts, and other teams to understand data requirements and provide technical support. - Collaborate with other engineering teams to seamlessly integrate data engineering solutions into larger cloud-based systems. Documentation : - Create and maintain comprehensive documentation for data engineering processes, cloud architecture, and pipelines. Technical Skills : Programming Languages : Proficiency in Python for data engineering tasks, scripting, and automation. Data Engineering Technologies : - Extensive experience with data engineering frameworks like distributed data processing. - Understanding and hands-on experience with workflow management tools like Apache Airflow. Cloud Platforms : - In-depth knowledge and hands-on experience with at least one major cloud platform: AWS, Azure, or Google Cloud. - Familiarity with cloud-native services for data processing, storage, and analytics. - ETL Processes : Proven expertise in designing and implementing Extract, Transform, Load (ETL) processes. - SQL and Databases : Proficient in SQL with experience in working with relational databases (e.g., PostgreSQL, MySQL) and cloud-based database services. - Data Modeling : Strong understanding of data modeling principles and experience in designing effective data models. - Version Control : Familiarity with version control systems, such as Git, for tracking changes in code and configurations. - Collaboration Tools : Experience using collaboration and project management tools for effective communication and project tracking. - Data Quality Assurance : Experience in implementing data quality checks and validation processes. - Agile Methodologies : Familiarity with agile development methodologies and practices. Soft Skills : - Strong problem-solving and critical-thinking abilities. - Excellent communication skills, both written and verbal. - Ability to work collaboratively in a cross-functional team environment. - Attention to detail and commitment to delivering high-quality solutions. If you possess the required technical skills and are passionate about leveraging cloud technologies for data engineering, we encourage you to apply.

Saras Analytics - Senior Data Engineer - Python (5-8 yrs)

We are seeking a highly skilled and motivated AI/ML Engineer to join our team. The ideal candidate will have extensive experience in developing, deploying, and optimizing machine learning models and pipelines. You will be responsible for automating workflows, transitioning proofs of concept (POCs) into production environments, and building scalable solutions such as customer segmentation, demand forecasting, and market mix models. Additionally, you will work with cutting-edge AI advancements, including Retrieval-Augmented Generation (RAG) and AI Agents, contributing to end-to-end automated Data Science solutions. Key Responsibilities: - Design, develop, and implement machine learning pipelines for automated workflows and customer insights generation. - Build and optimize predictive models for applications such as demand forecasting, inventory forecasting, and market mix modelling. - Develop natural language processing (NLP) modules leveraging techniques such as Retrieval-Augmented Generation (RAG) and AI Agents with LLMs. - Deploy machine learning models into production environments, ensuring scalability, reliability, and efficiency. - Transition POCs from experimentation to fully operational, production-grade systems. - Collaborate with cross-functional teams, including data scientists, engineers, and stakeholders, to translate business needs into ML solutions. - Apply containerization tools (e.g., Docker) and orchestration platforms (e.g., Kubernetes) for efficient deployment and lifecycle management of ML models. - Monitor, evaluate, and refine machine learning models to maintain performance and accuracy. - Stay updated on advancements in AI, machine learning, and data science technologies. Required Qualifications: - Bachelors or Masters degree in Computer Science, Machine Learning, Data Science, or a related field. - Proven experience in machine learning engineering or a similar role. - Proficiency in Python and its data science libraries. - Hands-on experience with ML frameworks such as PyTorch and TensorFlow. - Strong knowledge of data pre-processing, feature engineering, and model evaluation methodologies. - Understanding of NLP concepts, including pre-processing, embeddings, entity recognition, and vector storage. - Experience with containerization (Docker) and orchestration tools (Kubernetes). - Demonstrated ability to transition POCs into scalable production solutions. - Experience developing models for demand forecasting, inventory forecasting, or marketing analytics. - Familiarity with cloud platforms such as GCP and Azure, and their machine learning services. - Understanding of LLM architectures, statistical modelling, and advanced analytics techniques. - Proven ability to build, debug, and optimize large, high-performance ML training jobs. - Excellent problem-solving skills and a collaborative mindset. Preferred Skills: - Experience with CI/CD pipelines for ML model integration and deployment. - Familiarity with MLOps tools and practices. - Strong communication skills to explain technical concepts to non-technical stakeholders. What We Offer: - Competitive salary and comprehensive benefits package. - Opportunities to work on innovative and impactful AI projects. - A collaborative and inclusive work environment. - Continuous learning and professional development opportunities.

Others

Technical Requirements (Mandatory) - 2+ years of experience in relevant job roles - Excellent Communication skills and analytical skills - Excellent data interpretation skills, with proven track record deriving actionable business insights from large data sets - Proficiency in client communication and stakeholder management - Advanced general aptitude, problem solving and critical thinking ability - Experience creating executive presentations in PowerPoint - Experience performing cost-benefit analyses and creating proposals. - Working knowledge of SDLC lifecycle and collaborating with product teams. Understanding of : Data Manipulation tools - SQL and Excel - Visualization tools - At least one of PowerBI, Tableau, DataStudio/Looker - Cloud databases - BigQuery, Snowflake, Redshift or Azure - Working knowledge of Agile practices and sprint management in tools like JIRA or Asana. Behavioural Expectations (Mandatory) Individual traits essential to be successful in this role - - Self-motivation to work with abstract guidance. - Proactiveness to add business value. - Empathy to deal with multiple external and internal stakeholders. - Adaptability to work in cross-functional and high-performing teams. - Prioritization to visualize the big picture and maximize impact of outputs. - Perform RCAs and identify new data driven opportunities for adding business value or improving process productivity. - Communicate effectively about delivery: requirements, timelines, dependencies, priorities, etc. ensuring timely delivery without compromising on quality standards. - Act as an SME by leading trainings for business stakeholders and mentoring juniors as needed. Other Requirements (Preferred) - Bachelor's or master's degree in relevant fields like Computer Science Engineering, Finance, Statistics from reputed academic institutions - 1+ years of experience working in eCommerce or digitally native organizations. - Conceptual understanding of eCommerce/Omnichannel tools and platforms - Sales Channels - Shopify, Amazon, Walmart - Marketing - Customer Purchase Cycle - Analytics - Google Analytics Benefits - Competitive salary and performance-based bonuses. - Comprehensive health insurance, relocation benefits and other allowances - Professional development opportunities and continued learning - A collaborative and innovative work environment

Saras Analytics - Business Analyst (3-4 yrs)

Technical Requirements (Mandatory) - 5+ years of experience in relevant job roles - Excellent Communication skills and analytical skills - Excellent data interpretation skills, with proven track record deriving actionable business insights from large data sets - Proficiency in client communication and stakeholder management - Advanced general aptitude, problem solving and critical thinking ability - Experience creating executive presentations in PowerPoint - Experience performing cost-benefit analyses and creating proposals. - Working knowledge of SDLC lifecycle and collaborating with product teams. Understanding of : Data Manipulation tools - SQL and Excel - Visualization tools - At least one of PowerBI, Tableau, DataStudio/Looker - Cloud databases - BigQuery, Snowflake, Redshift or Azure - Working knowledge of Agile practices and sprint management in tools like JIRA or Asana. Behavioural Expectations (Mandatory) Individual traits essential to be successful in this role - - Self-motivation to work with abstract guidance. - Proactiveness to add business value. - Empathy to deal with multiple external and internal stakeholders. - Adaptability to work in cross-functional and high-performing teams. - Prioritization to visualize the big picture and maximize impact of outputs. - Perform RCAs and identify new data driven opportunities for adding business value or improving process productivity. - Communicate effectively about delivery: requirements, timelines, dependencies, priorities, etc. ensuring timely delivery without compromising on quality standards. - Act as an SME by leading trainings for business stakeholders and mentoring juniors as needed. Other Requirements (Preferred) - Bachelor's or master's degree in relevant fields like MBA, Computer Science Engineering, Finance, Statistics from reputed academic institutions - 2+ years of experience working in eCommerce or digitally native organizations. - Conceptual understanding of eCommerce/Omnichannel tools and platforms - Sales Channels - Shopify, Amazon, Walmart - Marketing - Customer Purchase Cycle - Analytics - Google Analytics Benefits - Competitive salary and performance-based bonuses. - Comprehensive health insurance, relocation benefits and other allowances - Professional development opportunities and continued learning - A collaborative and innovative work environment

Saras Analytics - Senior Business Analyst (5-7 yrs)

The Role : A Senior Business Analyst (SBA) in Saras Analytics plays a pivotal role in understanding and translating business needs into technical requirements. The SBA collaborates with stakeholders to gather and analyse data, identify trends, and contribute to the development and improvement of solutions. This role requires a combination of business acumen and technical proficiency to enhance the efficiency and effectiveness of the ecommerce platform. Behavioral Expectations (Mandatory) : - Self-motivated and proactive in adding business value - Empathetic in dealing with various stakeholders and adaptable to cross-functional, high performing teams - Ability to navigate abstract business problems through systematic data analysis and provide decision - Keen eye for detail and thorough with validation to ensure data sanctity - Creative individual eager to learn and apply new concepts, business models, and technologies Qualifications : - 4+ years of experience in data analysis projects using SQL and Excel - Exposure to BI tools such as PowerBI, Tableau, etc. - Experience with database design, data modeling and data mining Good To Have : - Bachelors degree in computer science, finance or statistics from reputed institutions - Experience in eCommerce or digitally native organizations - Experience with predictive analytics projects within the inventory and supply chain space - Proficiency in cloud databases like BigQuery and CRM Systems like Salesforce, NetSuite - Knowledge of the SDLC lifecycle and Scrum frameworks Benefits : - Professional development opportunities and continued learning - A collaborative and innovative work environment - Competitive salary and performance-based bonuses

Saras Analytics - Senior Business Analyst - SQL (4-8 yrs)

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