Data Scientist Manager

We are seeking an experienced Data Scientist Team Manager to lead hands-on development of Machine Learning, Generative AI, and advanced analytics solutions. The ideal candidate will combine strong technical expertise in Python, statistical modeling, LLMs, RAG, and NLP with the ability to manage a team, deliver scalable AI solutions, and translate business requirements into actionable insights.

The candidate will drive end-to-end model development, collaborate with cross-functional teams, mentor data science professionals, and ensure the successful deployment of AI-powered solutions.

Key Responsibilities

Machine Learning & Advanced Analytics

• Design, develop, and optimize machine learning models, predictive algorithms, and statistical models.
• Manage the end-to-end data science lifecycle, including data preparation, exploratory data analysis, feature engineering, model training, validation, deployment, and monitoring.
• Apply statistical techniques, experimentation, A/B testing, and predictive analytics to solve business problems.
• Evaluate model performance and improve accuracy, reliability, scalability, and efficiency.
• Work with large datasets and identify data quality issues, patterns, and business opportunities.

Generative AI, LLMs & NLP

• Develop and implement Generative AI applications using Large Language Models (LLMs).
• Design and implement Retrieval-Augmented Generation (RAG) solutions for enterprise use cases.
• Apply prompt engineering, embeddings, vector databases, and LLM evaluation techniques.
• Develop NLP solutions for intelligent search, content generation, automation, and information extraction.
• Explore frameworks and tools such as Hugging Face, LangChain, LangGraph, and other relevant AI technologies.

Team Management & Technical Leadership

• Lead and mentor data scientists and machine learning professionals.
• Allocate tasks, monitor progress, and ensure timely delivery of project milestones.
• Review code, model performance, and technical solutions to maintain quality standards.
• Establish best practices for experimentation, documentation, testing, and model development.
• Encourage knowledge sharing, innovation, and continuous improvement within the team.

Model Deployment & MLOps

• Collaborate with engineering and DevOps teams to deploy machine learning and AI models into production.
• Support model monitoring, retraining, versioning, and lifecycle management.
• Contribute to automated deployment pipelines and CI/CD practices.
• Ensure models meet performance, scalability, reliability, and security requirements.

Business Collaboration & Stakeholder Management

• Work with business and product stakeholders to understand requirements and identify suitable AI solutions.
• Translate analytical findings into actionable recommendations.
• Define project KPIs, model evaluation metrics, and business success criteria.
• Communicate technical concepts and project progress clearly to technical and non-technical stakeholders.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative discipline.
• 610 years of experience in Data Science, Machine Learning, AI, or advanced analytics.
• Strong programming skills in Python; experience with R is an advantage.
• Hands-on experience with Scikit-learn, TensorFlow, PyTorch, Hugging Face, or similar ML frameworks.
• Practical knowledge of statistical modeling, predictive analytics, feature engineering, and model evaluation.
• Experience developing Generative AI, LLM, NLP, or RAG-based applications.
• Strong understanding of SQL, data processing, and working with large datasets.
• Experience leading projects, mentoring team members, or coordinating technical teams.
• Good communication, analytical, problem-solving, and stakeholder management skills.

Preferred Qualifications

• Experience with LangChain, LangGraph, vector databases, embeddings, and prompt engineering.
• Exposure to cloud platforms such as GCP, Vertex AI, AWS, or Azure.
• Familiarity with MLOps, CI/CD pipelines, Docker, and model deployment practices.
• Experience with Apache Spark or other distributed computing technologies.
• Understanding of Responsible AI, data privacy, model bias, and AI governance.
• Prior experience working within Google or PLX environments is an advantage.

Key Competencies

• Machine Learning and Predictive Analytics
• Python and Statistical Modeling
• Generative AI, LLMs, and RAG
• NLP and Prompt Engineering
• Model Development and Deployment
• Team Management and Mentoring
• Project Execution and Delivery
• Stakeholder Communication
• Problem-Solving and Innovation

Why Join Us?

• Work on practical Machine Learning and Generative AI initiatives.
• Lead technical teams developing innovative AI-powered solutions.
• Solve complex business challenges using advanced analytics.
• Collaborate with experienced engineering, product, and business teams.
• Develop leadership expertise while working with emerging AI technologies.