We are looking to hire a talented Data Scientist with 5 to 8 years of experience to join our team and develop high-impact, scalable predictive analytics solutions. You will leverage advanced Gen AI, AI/ML to build solutions, build data pipelines, and be part of the productization team responsible for delivering robust solutions for our clients.

Responsibilities:

- Collaborate with business stakeholders, product managers, and engineering teams to translate business requirements into analytical solutions.

- Extract and integrate data from multiple sources through APIs, databases, and file-based interfaces.

- Analyze structured and unstructured data to identify trends, patterns, and actionable business insights.

- Perform data preprocessing, feature engineering, model development, deployment and model evaluation.

- Evaluate, fine-tune, and optimize AI/ML models to improve accuracy, performance, scalability, and reliability.

- Develop APIs and services for model deployment and integration with enterprise systems.

- Ensure data quality, governance, security, and compliance throughout the analytics lifecycle.

- Stay current with emerging AI, GenAI, machine learning, and data science technologies and recommend their adoption where appropriate.

Experience & Qualifications:

- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.

- 5 to 8 years of hands-on experience in Data Science, Machine Learning, Predictive Analytics.

- Strong proficiency in Python, including experience with data manipulation, statistical analysis, machine learning, and model development using libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch and related frameworks.

- Solid understanding of statistics, probability theory, hypothesis testing, regression analysis, sampling techniques, and experimental design to support data-driven decision making.

- Apply statistical and machine learning techniques to analyze large datasets, identify patterns, build predictive models, and generate actionable business insights.

- Experience with Generative AI technologies, Large Language Models (LLMs).

- Experience working with SQL and NoSQL databases, data warehouses, and big data technologies.

- Familiarity with cloud platforms such as AWS, and containerization technologies such as Docker and Kubernetes.

- Experience in building REST APIs and integrating AI models into production environments.

- Strong understanding of statistics, machine learning algorithms, forecasting techniques, and optimization methods.

- Excellent analytical, problem-solving, and communication skills with the ability to work in cross-functional teams.

Preferred Qualifications:

- Experience using graph technologies such as Neo4j and graph data modeling for fraud detection, relationship analysis, or customer intelligence.

- Familiarity with data governance, and data quality frameworks.

- Exposure to statistical methods and techniques for entity matching and identity resolution.