Posted on: 21/01/2026
Description :
- Apply techniques such as Bayesian methods, causal inference, probabilistic modeling, optimization, deep learning, and time-series analysis.
- Establish rigorous standards for experimentation, validation, and model evaluation.
- Collaborate with Engineering and MLOps teams to productionize models.
Technical & Strategic Leadership :
- Drive long-term data science and AI strategy and influence architectural decisions.
- Review and guide modeling approaches for high-impact initiatives.
Cross-Functional Collaboration :
- Communicate complex analytical findings to senior leadership and non-technical stakeholders.
Mentorship & Talent Development :
- Participate in hiring, technical evaluations, and peer reviews.
Required Qualifications :
- BE / BTech or equivalent in Engineering, Computer Science, Mathematics, or a related quantitative discipline.
- 15 to 18 + years of experience in applied data science or research-driven roles.
- Strong foundation in statistics, probability, and machine learning theory.
- Expert proficiency in Python and data science libraries (NumPy, Pandas, Scikit-learn).
- Experience with deep learning frameworks ( PyTorch , TensorFlow).
- Proven experience with experimental design, A/B testing, and causal inference.
Skills Required :
Referred / Nice-to-Have Skills :
- Experience with large-scale or distributed data systems (e.g., Spark).
- Domain expertise in NLP, recommender systems, computer vision, econometrics, or optimization.
- Exposure to GenAI / LLMs, including fine-tuning and evaluation.
- Experience working with production ML platforms and MLOps teams.
About Symplr :
Did you find something suspicious?