Senior Data Scientist

Experience:- 6- 9 Years Location:- Mumbai (Onsite) Notice:- Immediate to 30 Days Roles &; Responsibilities: Cross-Functional Collaboration: Partner with business, operations, pricing, and sales teams to identify and prioritize high-impact opportunities for ML, AI, and GenAI-driven solutions. End-to-End Project Ownership: Lead data science initiatives from problem definition and ideation through development, deployment, and business adoption, ensuring timely and high-quality delivery. Solution Architecture: Design scalable, robust, and production-ready ML and GenAI solutions aligned with business objectives, with a strong focus on measurable impact and ROI. Hands-On Model Development: Build, validate, and optimize machine learning and AI models using state-of-the-art techniques, ensuring adherence to best practices in model development and experimentation. Stakeholder Communication: Translate complex analytical outputs into clear, actionable insights and present recommendations effectively to senior stakeholders and leadership teams. Deployment & Integration: Collaborate with data engineering and platform teams to operationalize models and integrate AI solutions seamlessly into business workflows and systems. Performance Monitoring & Optimization: Establish monitoring frameworks to track model performance, ensure reliability, and drive continuous improvement through retraining and refinement. Mentorship & Team Leadership: Mentor and guide junior data scientists and analysts, fostering technical excellence, structured problem-solving, and a culture of continuous learning. DESIRED CANDIDATE PROFILE: Educational Background: Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field (BE/BTech/MSc/MTech/PhD), with 5–6 years of relevant experience in Data Science, Machine Learning, and AI/GenAI solution development. Technical Proficiency: Strong programming skills in Python and SQL, with hands-on experience in building end-to-end data science solutions. Familiarity with modern ML frameworks and libraries is expected. AI/ML & GenAI Expertise: Proven experience across Machine Learning, Deep Learning, and Generative AI, with a strong track record of translating business problems into scalable, real-world AI solutions. Cloud & Data Engineering Skills: Practical experience with cloud platforms (preferably AWS), along with exposure to big data technologies such as Spark. Working knowledge of scalable data pipelines and MLOps practices is a plus. Data Management & Databases: Strong understanding of structured and unstructured data, with hands-on experience in SQL and NoSQL databases, and efficient data processing and retrieval techniques. Analytical & Problem-Solving Skills: Strong analytical thinking with the ability to break down complex problems, apply structured approaches, and deliver innovative, data-driven solutions. Communication & Stakeholder Management: Excellent communication and storytelling skills, with the ability to translate complex technical concepts into clear business insights for both technical and non-technical stakeholders.