We are looking for an experienced Data Scientist to join our team and contribute to critical projects across a variety of domains. This role requires a hands-on technologist who can demonstrate strong communication and collaboration skills and work effectively in a cross-functional environment.

Our approach to hiring for Data Science roles is focused on clearly defined topic areas, ensuring alignment between project needs and candidate strengths. You’ll be evaluated and assigned to projects based on specific skillsets required, not a one-size-fits-all model.

Key Responsibilities:

• Apply data science techniques to solve real-world business problems across multiple domains
• Work on clearly scoped topic areas such as Classical ML, Deep Learning, Optimization, or LLM/RAG depending on the project requirements
• Demonstrate strong hands-on coding and data analysis skills throughout the interview and project lifecycle
• Communicate findings and collaborate effectively with both technical and non-technical stakeholders
• Participate in structured feedback loops and continuously improve based on input from peers and interviewers

Topic Areas (Role-Specific Focus Will Be Provided):

Candidates will be assessed based on the topic areas relevant to the role they’re being considered for. Not all topic areas are required for all roles.

• Classical Machine Learning(e.g., supervised/unsupervised learning, regression, clustering)
• Deep Learning(primarily fine-tuning existing models, not training from scratch)
• Optimization(e.g., linear programming, non-linear optimization)
• LLMs / Retrieval-Augmented Generation (RAG)(understanding of LLM application, prompt engineering, integration with retrieval systems)