Lead Data Scientist

Data Scientist

Full-Time | 10+ Years Experience | AI / ML / Deep Learning / LLMs

ABOUT THE ROLE

We are looking for a seasoned Data Scientist to join our growing team in Mumbai. The ideal candidate brings over 10 years of hands-on experience across the full data science lifecycle from exploratory analysis and model development to deploying large-scale AI solutions in production. You will work on cutting-edge projects involving LLMs, computer vision, image processing, and multi-source data integration.

KEY RESPONSIBILITIES

• Design, develop, train, and deploy machine learning, deep learning, and AI models at scale.
• Deploy and fine-tune Large Language Models (LLMs) using open-source frameworks (LLaMA, Mistral, Falcon, etc.).
• Build and integrate pipelines using public and internal APIs to enable end-to-end AI workflows.
• Work on computer vision projects including image processing, object detection, and YOLO-based detection algorithms.
• Apply statistical modeling and advanced analytical techniques to solve complex business problems.
• Integrate multiple data sources into unified, production-ready data systems.
• Collaborate cross-functionally with engineering, product, and business teams to translate requirements into AI solutions.
• Stay current with the latest open-source models, research papers, and industry trends.
• Provide technical leadership, mentorship, and code reviews within the data science team.

REQUIRED SKILLS & QUALIFICATIONS

• Experience: 10+ years in Data Science, Machine Learning, or AI-focused roles.
• Languages & Tools: Expert-level proficiency in Python and SQL.
• LLMs: Hands-on experience deploying and fine-tuning large language models; familiarity with HuggingFace, LangChain, or similar ecosystems.
• ML & AI: Deep knowledge of statistical modelling, classical ML algorithms, and modern AI architectures.
• Deep Learning: Proven experience with deep learning frameworks (PyTorch, TensorFlow/Keras).
• Computer Vision: Practical experience in image processing, object detection, segmentation, and YOLO-based algorithms.
• APIs: Strong experience building and consuming RESTful and third-party APIs for AI integration.
• Open Source Models: Comfortable exploring, evaluating, and adapting open-source models for production use.
• Cloud: Working knowledge of AWS (SageMaker, S3, EC2, Lambda or equivalent services).
• Data Integration: Ability to integrate and harmonize multiple heterogeneous data sources into a single system.

GOOD TO HAVE

• GIS & Geospatial: Knowledge of GIS tools and geospatial data (e.g., QGIS, GeoPandas, PostGIS, satellite imagery analysis) is a strong plus.
• Open Source Exploration: Enthusiasm and proven track record of experimenting with and contributing to open-source ML/AI projects.
• Frontend Basics: Familiarity with HTML and CSS for prototyping dashboards or demo interfaces.
• MLOps: Experience with model versioning, monitoring, and CI/CD pipelines for ML (MLflow, Kubeflow, etc.).
• Visualization: Proficiency in data visualization tools ( Plotly, Power BI, or Tableau).