Advanced Data Science Associate
DATA SCIENCE ASSOCIATE
Data Science Associate (DSA) design, develop and execute high-impact analytics solutions for large, complex, structured and unstructured data sets (including big data) to help clients make better fact-based decisions.
Responsibilities:
- 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, optimizing 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 data science workflows.
Qualifications:
- Bachelor's or master's degree or PhD in Computer Science (or Statistics) from a premier institute, and strong academic performance with analytic and quantitative coursework is required.
- 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 modeling, 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.
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