Principal Data Scientist

We are seeking a Principal Data Scientist with a strong research background and deep expertise in advanced machine learning and statistical modeling. This role requires the ability to translate theoretical research into scalable, real-world solutions while providing technical leadership across data science initiatives. You will lead complex modeling efforts, influence data science strategy, and mentor senior talent. 

Advanced Modeling & Research 

• Design and lead development of advanced ML and statistical models for complex business problems. 

• 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 

• Serve as a Principal-level authority on data science methodologies and best practices. 

• Drive long-term data science and AI strategy and influence architectural decisions. 

• Review and guide modeling approaches for high-impact initiatives. 

Cross-Functional Collaboration 

• Partner with Product, Engineering, and Business teams to frame ambiguous problems into data-driven solutions. 

• Communicate complex analytical findings to senior leadership and non-technical stakeholders. 

Mentorship & Talent Development 

• Mentor senior and staff-level data scientists and guide research excellence. 

• Participate in hiring, technical evaluations, and peer reviews. 

Required Qualifications 

• PhD (Preferred) in Computer Science, Statistics, Mathematics, Physics, Economics, or related field 

• 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. 

Preferred / Nice-to-Have Skills 

• Publications in top-tier ML or data science conferences/journals. 

• 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: 

As a leader in healthcare operations solutions, we empower healthcare organizations to navigate the complexities of integrating critical business operations. Our customers are at the heart of everything we do, and they rely on our mission-critical systems to drive better operations and better outcomes. 

We are a remote-first company with employees working across the United States, India, and the Netherlands. Guided by values, we focus on teamwork, championing our customers, being rooted in action and outcomes, overcoming challenges, and leading through equality and integrity. Read more about symplr's culture and values at symplr.com/careers.