About the role
• Develop advanced algorithms that solve problems of large dimensionality in a computationally efficient and statistically effective manner
• Execute statistical and data mining techniques (e.g. hypothesis testing, machine learning and retrieval processes) on large data sets to identify trends, figures and other relevant information
• Collaborate with clients and other ZS stakeholders to effectively integrate and communicate analysis findings
• Contribute to the evaluation of emerging datasets and technologies that may contribute to our analytical platform
• Evaluating emerging datasets and technologies that may contribute to our analytical platform
• Owning the development of select assets/accelerators for efficient scaling of capability, with a focus on leveraging generative AI and deep learning methodologies.
• Integrate engineering principles into data science workflows, optimising algorithms for performance, scalability, and maintainability.
• Collaborate with the engineering team to implement and deploy data science solutions into production, ensuring seamless integration with existing systems.
• Utilize software engineering best practices for version control, code review, testing, and documentation to maintain high-quality, reliable, and reproducible
RequirementsQualifications:
- Experience Range: We are targeting candidates with 6 months to 3 years of experience. Candidates who have 7 or more CGPA.
- Education Criteria: B.E/B.Tech, M.E/M.Tech (any stream), B.Sc /M.Sc (Statistics & Mathematics)
- Candidate should have worked with end to end model building (development to deployment from scratch), machine learning algorithms (regressions, random forest, decision tree, XGBoost Model) and strong hands on experience working with Python.
- 1-3 years of Data Science experience, including proficiency in generative AI, deep learning, statistical techniques, and engineering integration for scalable solutions.
- Knowledge of programming (e.g. Java/Python/R);
- Knowledge of big data/advanced analytics concepts and algorithms (e.g. text mining, social listening, recommender systems, predictive modelling, etc.);
- Excellent oral and written communication skills.
- Strong attention to detail, with a research-focused mindset;
- Excellent critical thinking and problem-solving skills;
- High motivation, good work ethic and maturity.
- Exposure to Generative AI and its usage to solve problems is a plus.