What are the responsibilities and job description for the Lead Data Scientist position at EXL?
Lead Data Scientist – Reinforcement Learning (Philadelphia, Hybrid, EST)
We need a Lead Data Scientist with 6 years in data science (not software development or QA) who has built reinforcement learning (RL) models and delivered them in real-world settings. You will lead RL projects from start to finish and guide a small team of data scientists.
Key Responsibilities:
- Build RL Models: Develop and deploy reinforcement learning models for complex problems. Define states, actions, rewards, and train RL algorithms to optimize real-world outcomes.
- Production Focus: Work with engineers to turn models into production systems, ensuring they perform well at scale (monitoring, tuning, A/B testing).
- Innovation: Stay up-to-date on advanced RL techniques (like policy gradients, Q-learning) and bring the best ideas to our projects.
- Team Leadership: Mentor junior data scientists. Review their code and models. Foster a culture of experimentation and learning.
Required Qualifications:
- Experience: 6 years in data science or machine learning roles (not software developer, systems analyst, or tester positions).
- Reinforcement Learning (Must-Have): Hands-on experience building RL models and using them in real applications. This is required for the role.
- Technical Skills: Strong Python programming and ML libraries (e.g., PyTorch or TensorFlow). Familiar with RL tools/frameworks (like OpenAI Gym, Ray RLlib, etc.). Good understanding of algorithms, statistics, and how to design experiments.
- Problem-Solving: Proven track record of solving complex problems with data and ML. Able to break down business challenges and use data and RL to solve them.
- Communication: Clear collaborator who can explain technical ideas to non-technical partners. Experience guiding other data scientists is a plus.
- Education: Bachelor’s or Master’s in a relevant field (e.g., Computer Science, Data Science, Math, Engineering).
Location & Schedule: Philadelphia area (hybrid)
Why This Role: You’ll be the go-to person for Reinforcement Learning on our team. You’ll tackle interesting projects, lead innovation, and see your models make a real-world impact.