Meaningful work,
meaningful life

Key Responsibilities

• Collaborate with business stakeholders to understand use cases and define problem statements.

• Design and implement end-to-end AI/ML solutions, including:

  • Data collection, cleaning, and preprocessing

  • Feature engineering and model selection

  • Model training, evaluation, and deployment

• Work on challenging prediction problems, such as:

  • Predicting sales for products with irregular demand patterns (e.g., high sales for a few days followed by long periods of no sales)

• Develop scalable and maintainable ML pipelines.

• Continuously research and apply the latest AI/ML techniques to new business problems.

• Communicate insights and results effectively to both technical and non-technical stakeholders.

Required Skills & Qualifications

• Strong proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).

• Solid understanding of statistical modeling, time-series forecasting, and predictive analytics.

• Experience with data preprocessing, handling imbalanced datasets, and feature engineering.

• Knowledge of cloud platforms (AWS, Azure, GCP) and ML deployment tools.

• Ability to work on non-standard prediction problems where patterns are irregular or sparse.

• Excellent problem-solving and analytical skills.

• Strong communication and collaboration abilities.

Preferred Qualifications

• Experience with deep learning, NLP, or reinforcement learning.

• Familiarity with MLOps and CI/CD for ML models.

• Exposure to business analytics and understanding of revenue-impacting use cases.