We are looking for a highly skilled and results-driven Data Scientist to join our data and analytics team. The ideal candidate will be responsible for designing and implementing advanced machine learning and AI models to solve real-world business problems. You will work closely with cross-functional teams to gather data, build predictive and prescriptive models, and communicate insights that inform strategic decisions. Your expertise will help drive innovation and data-driven transformation across the organization.

Key Responsibilities :

- Collect, clean, and preprocess structured and unstructured data from diverse internal and external sources.

- Perform data wrangling, missing value imputation, feature engineering, and data transformation to prepare datasets for analysis and modeling.

- Work with large-scale datasets from relational databases, APIs, cloud sources, or raw files (e.g., CSV, JSON, logs, text).

Develop and deploy machine learning (ML) and AI models for :

- Classification, regression, clustering

- Recommendation systems

- Anomaly detection and forecasting (as needed)

- Perform model selection, hyperparameter tuning, cross-validation, and evaluation using best practices.

- Use AWS SageMaker, H2O.ai, or in-house tools to train, evaluate, and deploy models at scale.

- Package and deploy models as APIs or batch processes, integrating them into business workflows or applications

- Apply descriptive statistics, inferential statistics, and hypothesis testing to derive insights from data.

- Design experiments (e.g., A/B testing) and analyze their results.

- Translate business challenges into quantitative frameworks and model-driven solutions.

- Continuously track model performance (e.g., drift, degradation, real-world impact).

- Re-train, re-tune, or retire models as needed to maintain accuracy and relevance.

- Implement model versioning, logging, and audit trails for traceability.

- Work with stakeholders from product, marketing, engineering, and business teams to understand needs and define solutions.

- Present analytical results, data-driven recommendations, and visualizations to non-technical audiences.

- Document solutions, processes, assumptions, and results clearly and concisely.

Required Skills & Qualifications :

- 3 - 6 years of experience in a Data Science or Machine Learning role.

Strong programming skills in Python, including libraries such as :

- NumPy, pandas, scikit-learn

- matplotlib, seaborn (for visualization)

- Solid command of SQL for querying, transforming, and analyzing data from relational databases.

- Experience deploying models using AWS SageMaker or similar cloud platforms.

- Familiarity with H2O.ai tools and automated machine learning (AutoML) frameworks.

- Strong understanding of statistical theory, data distributions, bias/variance trade-offs, and model evaluation metrics.

- Proficiency in the full ML lifecycle: from data exploration and feature engineering to deployment and monitoring.