Senior Data Scientist
- Frame use cases with business teams, validate data availability, and define the right approach.
- Design and implement machine learning or generative AI solutions that create measurable business impact.
- Ensure solutions are robust, scalable, and production-ready by applying software engineering and MLOps best practices.
- Translate business requirements into robust AI pipelines and architectures.
- Promote best practices in coding, testing, and deployment to guarantee maintainability and scalability.
- Explore and apply advanced AI techniques to solve complex client problems.
- Explain AI approaches in clear and pragmatic terms, highlighting feasibility, risks, and ROI.
- Build strong relationships with client stakeholders, from operational teams to managers.
- Act as a go-to expert for technical guidance within projects.
- Mentor junior data scientists, provide feedback, and support their growth.
- Share best practices through workshops, documentation, and informal training sessions.
- Contribute to internal accelerators and tools to increase delivery efficiency across projects.
- Maintain active technology watch and bring new methods, tools, and frameworks into practice.
- 3+ years of hands-on experience developing and deploying data-driven solutions.
- Strong knowledge in applied machine learning and generative AI.
- Solid understanding of software engineering and MLOps best practices.
- Experience delivering AI projects in cloud environments.
- Show intellectual curiosity and structured problem-solving.
- Approach challenges with pragmatism and creativity.
- Bridge the gap between business stakeholders and technical teams.Deliver with autonomy and reliability, ensuring client satisfaction.Share knowledge and mentor more junior colleagues.Build trust with clients through clear communication and rigor.
- HR call
- Standard Interview
- Technical Interview
- Fit Interview
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