Data Science & AI Solutions

Lead the development of predictive, prescriptive, and generative AI solutions to address business challenges.

Design and implement machine learning, deep learning, and statistical models.

Develop frameworks for feature engineering, model training, evaluation, and deployment.

Evaluate emerging AI/ML technologies and recommend adoption opportunities.

Engineering & Architecture

Design scalable data science and machine learning architectures.

Build production-ready ML pipelines and model serving frameworks.

Collaborate with data engineering teams to establish robust data pipelines and feature stores.

Ensure solutions adhere to enterprise architecture, security, and governance standards.

MLOps & Operationalization

Establish model lifecycle management processes including CI/CD, monitoring, versioning, retraining, and explainability.

Implement model performance tracking, drift detection, and automated retraining mechanisms.

Drive adoption of MLOps best practices and tooling.

Leadership & Collaboration

Lead and mentor a team of data scientists and machine learning engineers.

Partner with business stakeholders, product owners, architects, and engineering teams to translate requirements into data science solutions.

Provide technical leadership through design reviews, code reviews, and best-practice guidance.

Drive estimation, planning, prioritization,



and delivery of data science initiatives.

Governance & Compliance

Ensure responsible AI practices, model governance, fairness, explainability, and regulatory compliance.

Define standards for model documentation, validation, and auditability.

Required Qualifications

Education

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

Experience 8-12+ years of experience in software engineering, data science, or machine learning.

3+ years leading teams or managing data science initiatives.

Experience delivering production-grade machine learning solutions at scale.

Technical Skills

Programming

Python, SQL

Experience with Spark/PySpark is preferred.

Machine Learning & AI

Supervised and unsupervised learning

Deep learning frameworks (TensorFlow, PyTorch)

NLP, LLMs, RAG, Agentic AI

Time series forecasting, recommendations, optimization techniques

Data & Analytics

Feature engineering

Statistical analysis and hypothesis testing

Experimentation and A/B testing

Data visualization and storytelling

Cloud & MLOps

AWS, Azure,

Docker, Kubernetes

MLflow, Airflow ,SageMaker, Azure ML, or equivalent

CI/CD pipelines and model deployment frameworks

Soft Skills

Robust analytical and problem-solving skills.

Excellent communication and stakeholder management.

📌 Agentic AI Lead (Bengaluru)
🏢 Indegene
📍 Bengaluru