We are seeking a highly motivated Senior Data Scientist to develop data-driven solutions, build machine learning models, and generate actionable insights that drive business growth.

The ideal candidate will possess strong expertise in data science, statistical modeling, machine learning, and cloud-based data platforms, with the ability to translate complex business challenges into scalable analytical solutions.

Key Responsibilities :

- Design, develop, and deploy machine learning and advanced analytics solutions to solve business problems and improve decision-making.

- Conduct exploratory data analysis (EDA) to identify trends, patterns, anomalies, and actionable insights from large and complex datasets.

- Develop predictive, classification, clustering, forecasting, and recommendation models using statistical and machine learning techniques.

- Collaborate with business stakeholders, product teams, and engineering teams to understand requirements and deliver data-driven solutions.

- Design, build, and maintain scalable data pipelines and data processing workflows using AWS services and modern data engineering practices.

- Work with structured and unstructured data from multiple sources to support analytics and machine learning initiatives.

- Evaluate model performance, perform feature engineering, and optimize algorithms to improve accuracy and business impact.

- Deploy, monitor, and maintain machine learning models in production environments.

- Communicate analytical findings, recommendations, and business insights through reports, dashboards, and executive presentations.

- Ensure data quality, governance, and compliance standards are maintained throughout the analytics lifecycle.

- Stay current with emerging trends in Data Science, Artificial Intelligence, Machine Learning, and cloud technologies.

Required Skills & Experience :

- 5-9 years of experience in Data Science, Machine Learning, Advanced Analytics, or related fields.

- Strong programming skills in Python and SQL; experience with R is an added advantage.

- Hands-on experience with machine learning libraries and frameworks such as Scikit-learn, TensorFlow, PyTorch, or similar.

- Strong understanding of statistical analysis, predictive modeling, and data mining techniques.

- Experience working with large datasets and building scalable analytics solutions.

- Hands-on experience with AWS services such as S3, Lambda, Step Functions, and other cloud-native data services.

- Experience designing and maintaining data pipelines and ETL workflows.

- Strong knowledge of data visualization and reporting tools.

- Excellent analytical, problem-solving, and communication skills.

- Ability to effectively communicate technical concepts and insights to both technical and non-technical stakeholders.

Preferred Skills :

- Experience with MLOps, model deployment, and monitoring frameworks.

- Exposure to Generative AI, LLMs, NLP, or Deep Learning use cases.

- Experience with Spark, Databricks, or distributed data processing platforms.

- Familiarity with Docker, Kubernetes, and CI/CD practices.

- Experience working in Agile development environments.

Ideal Candidate :

- A results-driven Data Scientist who combines strong analytical capabilities, machine learning expertise, and cloud-based data engineering experience to deliver scalable solutions and measurable business impact.