Data Science Manager

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Role Overview

Manager Data Science

You will partner closely with Product, Engineering, and Business stakeholders to scale reliable, explainable, and high-quality data products.

Key Responsibilities

Team Leadership & Development

• Coach, mentor, and develop a high-performing team of data scientists and ML engineers.
• Foster a culture of continuous learning, experimentation, and technical excellence.
• Act as a technical mentor and subject-matter expert for complex modeling challenges.

Project & Delivery Management

• Plan projects, prioritize initiatives, allocate resources, and track milestones to ensure timely delivery.
• Balance short-term delivery with long-term platform and capability building.
• Drive accountability, quality, and impact across all data science deliverables.

Technical & MLOps Leadership

• Provide technical guidance on

  model selection, architecture, feature engineering, evaluation, and deployment

  .
• Ensure best practices for

  model monitoring, versioning, CI/CD pipelines, and MLOps

  .
• Oversee deployment and maintenance of models in production environments.

Innovation & Strategy

• Stay current with industry trends in AI/ML, NLP, and Generative AI.
• Sponsor prototyping, experimentation, and adoption of new methods where appropriate.
• Drive scalable, explainable, and efficient ML solutions aligned with business goals.

Core Skills

• Natural Language Processing (NLP) & Large Language Models (LLMs)
• Machine Learning & Statistical Modeling
• Python & SQL
• Information Retrieval & Semantic Search
• Data Visualization & Communication
• MLOps & Model Lifecycle Management
• AWS & Cloud-Based ML Systems
• Software Engineering Best Practices

Technical Abilities

• Advanced proficiency in

  statistical analysis and machine learning

  .
• Deep expertise in

  NLP, Generative AI, and LLMs

  .
• Experience with

  LLM efficiency techniques

  (quantization, distillation, pruning).
• Familiarity with

  GPU acceleration and distributed training

  .
• Strong experience deploying and maintaining models in production.
• Excellent problem-solving and performance-optimization mindset.
• Strong written, verbal, and cross-functional communication skills.

Education & Experience

• Bachelor's degree in

  Computer Science, Statistics, Mathematics, Engineering, or related field

  .
• (Master's or PhD preferred but not mandatory.)
• 6+ years of experience in

  Data Science, Machine Learning, or Analytics

  .
• Minimum 2 years of experience in a

  people-management or team-lead role

  .
• Proven track record of shipping ML/data products to production with measurable business impact.