Lead Data Scientist

Job Description: Data Scientist

Experience Required:
7+ years in IT, 3+ years in Gen AI

Skills - Core ML, Python, Basic Gen AI, Model Deployment

Location:
Mumbai (In Office)

About the Role

We're seeking a Data Scientist to develop and deploy machine learning solutions that drive business impact. You'll work across the full ML lifecycle—from problem definition and data exploration to model development, deployment, and monitoring—collaborating with engineers, analysts, and stakeholders to translate data into actionable insights.

Key Responsibilities

• Model Development & Experimentation:

Build, train, and optimize
ML models
for prediction, classification, and recommendation.

Explore and prototype
Generative AI
solutions using LLMs and embeddings.

Work with
Python, TensorFlow / PyTorch, Scikit-learn, Pandas, NumPy

• Data Pipeline & Feature Engineering:

Build and maintain robust data pipelines; create meaningful features for model training and production inference

• Model Deployment & MLOps:

Deploy models on
AWS / Azure / GCP

using services like
SageMaker, Vertex AI, or Azure ML

.

• Stakeholder Collaboration:

Work with product, engineering, and business teams to translate requirements into technical solutions; communicate findings and model performance to non-technical audiences

• Research & Optimization:

Stay current with ML advancements; experiment with new techniques and tools to improve model accuracy, efficiency, and scalability

• Documentation & Best Practices:

Maintain code quality, version control, and comprehensive documentation for reproducibility and knowledge sharing

Required Qualifications

• 7 years of professional experience in IT with
  4+ years machine learning, data science, or related quantitative role
• Strong proficiency in Python
  and familiarity with ML libraries.
• Hands-on with Python, TensorFlow, PyTorch, Scikit-learn, NLP / GenAI frameworks (LangChain, Hugging Face)
• Explore and prototype
  Generative AI
  solutions using LLMs and embeddings.
• Collaborate with data engineers and business teams to translate insights into action.
• Solid understanding of core ML concepts: supervised/unsupervised learning, model evaluation, cross-validation, hyperparameter tuning
• Experience building and deploying models to production (cloud platforms, REST APIs, containers, or similar)
• Hands-on experience with data pipelines
  and ETL processes
• Ability to communicate complex findings clearly to technical and non-technical stakeholders
• Familiarity with cloud platforms
  (AWS, GCP, Azure)
  using services like
  SageMaker, Vertex AI, or Azure ML
• Experience with MLOps tools (MLflow, DVC, Airflow, or similar)
• Strong understanding of data preprocessing, feature engineering, model evaluation, and deployment
• Experience with
  SQL, APIs, and data visualization tools (Power BI, QuickSight, etc.) is a plus.
• Knowledge of deep learning and neural networks
• Background in data engineering or systems thinking
• Experience with A/B testing and experimentation frameworks
• Advanced degree (Master's/PhD) in Computer Science, Statistics, Mathematics, or related field

What We're Looking For

• Pragmatist mindset
  : Can balance model sophistication with business needs and implementation timelines
• Curiosity
  : Actively learns new tools and techniques; stays informed about industry developments
• Collaboration:
  Thrives in cross-functional teams; communicates technical concepts clearly
• Ownership:
  Takes end-to-end responsibility for projects from conception to production monitoring
• Bias toward action:
  Can prototype quickly, iterate based on feedback, and deliver incrementally

What We Offer

• Competitive salary and benefits package
• Opportunity to work on challenging, high-impact problems
• Collaborative, learning-focused environment
• Professional development support and conference attendance