What are the responsibilities and job description for the Data Scientist position at Tata Technologies?
Data Scientist
Detroit, MI
Job Description:
About the Role
We are seeking an experienced Data Scientist to lead the design, development, and deployment of advanced analytics, AI, and GenAI solutions. This role requires strong technical leadership, deep expertise in statistical and machine learning methods, and the ability to architect scalable analytics systems that deliver measurable business value.
Key Responsibilities:
- Lead end-to-end analytics solution design, ensuring scalable and production-ready implementation.
- Apply advanced statistical and machine learning techniques to develop models that solve complex business problems.
- Build and maintain cloud-based data pipelines and analytics workflows across modern data platforms.
- Develop and deploy AI and GenAI solutions including LLMs, RAG pipelines, and prompt-driven applications.
- Deliver production-grade digital analytics products using Python, Snowflake, Alteryx, and visualization tools.
- Collaborate with business and technical partners to translate insights into actionable recommendations.
- Provide technical leadership, mentorship, and guidance to data science and engineering teams.
Required Qualifications:
- 8 years of experience in data science, machine learning, or AI engineering.
- Strong proficiency in Python, statistical modeling, and ML algorithms.
- Hands-on experience with cloud data engineering (AWS, Azure, Snowflake).
- Demonstrated expertise in GenAI, LLMs, RAG, and prompt engineering.
- Experience with interactive analytics visualization (Power BI, Alteryx).
- Proven ability to design and deploy production-grade analytics systems.
- Excellent communication and stakeholder-influencing skills.
Preferred Qualifications
- Master’s or PhD in Data Science, Statistics, Computer Science, Engineering, or related field.
- Experience with MLOps, CI/CD pipelines, and model monitoring.
- Experience leading enterprise-scale analytics or AI initiatives.
- Familiarity with industrial, manufacturing, or IoT/telematics data environments.