Manager of Data Science (Hybrid)

As the Manager of Data Science, you will lead and grow a team of data scientists and machine-learning engineers to design, build, and productionize analytics and ML solutions that drive business outcomes. You will be a hands-on technical leader who balances people management, project delivery, and strategic direction—partnering with product, engineering, and business stakeholders to scale reliable, explainable, and measurable data products.

Major Responsibilities:

• Coach, mentor, develop and lead a high performing data science team.
• Plan projects, prioritize work, allocate resources, and track milestones to ensure timely delivery of data science projects and deliverables.
• Provide technical guidance on model selection, model architecture, feature engineering, evaluation, and productionization.
• Ensure best practices for model monitoring, versioning, CI/CD and MLOps.
• Keep the team current with industry trends and appropriate new methods; sponsor prototyping and experimentation.
• Serve as a technical mentor and subject-matter expert for complex modeling problems.

Education & Experience:

• Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or related field (Master’s/PhD preferred).
• 6+ years of experience in data science, machine learning, or analytics; 2+ years in a leadership or management role.
• Proven track record of deploying ML/AI products to production with measurable business impact.
• Expertise in Natural Language Processing (NLP), Generative AI, and Large Language Models (LLMs).
• Skilled in statistical modeling, machine learning, and model efficiency techniques (e.g., quantization, distillation, pruning).
• Proficient in Python and SQL; experienced in information retrieval, semantic search, and data visualization.
• Knowledge of MLOps practices, model deployment, and maintenance in production environments.
• Familiar with GPU acceleration, distributed training, and cloud platforms (e.g., AWS).
• Strong foundation in software engineering best practices and performance optimization.
• Demonstrated leadership, project/resource management, and cross-functional collaboration skills.
• Excellent written and verbal communication abilities.