Data Scientist

The Senior/Lead Data Scientist will design and deploy large-scale analytics solutions that deliver measurable impact. This role leads data-driven projects from ideation through implementation, provides technical and strategic guidance, and ensures best practices in data science across the business.

• Lead end-to-end advanced analytics and data science projects, delivering actionable insights and predictive models.
• Manage, mentor, and provide guidance to junior and mid-level data scientists.
• Collaborate with business stakeholders to translate strategic objectives into data-driven solutions and drive the data strategy.
• Apply advanced statistical, machine learning, and deep learning techniques for problem solving.
• Oversee data management, data governance, and pipeline design to ensure high data quality and reliability.
• Develop, validate, and deploy production-grade models for business problems acrossIoT, product analytics, and AI domains.
• Hands-on solutioning knowledge of Large Language Models (LLMs), fine-tuning, and RAG (Retrieval Augmented Generation) frameworks for enterprise AI applications.
• Present findings and recommendations to business teams, including creation of clear visualizations and non-technical reports.
• Stay abreast of the latest data science, analytics, and AI/ML trends and industry best practices.

• 7 10 years of experience in data science, analytics, or ML application roles.
• Expertise with Python, R, SQL, and advanced machine learning libraries (TensorFlow, PyTorch, Scikit-learn).
• Strong statistical and mathematical modeling background (regression, classification, clustering, deep learning, time series).
• Hands-on experience with Big Data technologies (Spark) and data pipeline design.
• Track record of leading successful analytics projects and collaborating cross- functionally.
• Excellent communication, visualization, and storytelling skills for technical and non-technical audiences.
• Proven ability to manage teams, mentor junior talent, and foster a collaborative culture.

• Experience in IoT, product engineering, or high-tech environments.
• Familiarity with cloud platforms and scalable model deployment (AWS, Azure, GCP).
• Knowledge of MLOps, containerization (Docker, Kubernetes), and version control (Git).
• Professional certifications in data science, ML/AI, or project management.

• 7-10 Years