Data Science Associate Consultants (DSAs) 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.
What You'll Do
- Stay updated with the latest developments in Deep Learning and AI research.
- Implement and fine-tune advanced models in deep learning, with a focus on Transformers for sequential data (e.g., time series, text, and vision).
- Apply knowledge of large language model (LLM) fine-tuning and alignment approaches to improve model performance.
- Utilize active learning techniques to train models more efficiently and effectively.
- Collaborate with cross-functional teams to develop and deploy machine learning models in production.
- Contribute to research projects aimed at advancing the field of AI and machine learning.
- Develop advanced algorithms that solve problems of large dimensionality in a computationally efficient and statistically effective manner.
- 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.
- Own 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.
What You'll Bring
- 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.
- 4-7 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.
