Lead Data Scientist - Artificial Intelligence/Machine Learning

Data Science Manager

We're seeking a seasoned Data Science Manager to lead a high-performing team guiding projects from conception through deployment to drive measurable business impact. You'll steer strategic alignment of ML initiatives, mentor talent, and collaborate closely with stakeholders to deliver scalable AI solutions.

Responsibilities :

- Prioritize and manage ML projects in alignment with business goals for efficient delivery.

- Design end-to-end ML systems spanning data collection, modeling, testing, deployment, and maintenance.

- Drive the adoption of state-of-the-art research and academic papers into practical solutions.

- Develop impactful generative AI and LLM-based applications using frameworks like LangChain and LlamaIndex.

- Engage with clients and stakeholders through high-level presentations and technical consultations.

Requirements :

- Technical Leadership : 7+ years in data science/ML, including team oversight and project planning.

- ML Research & Implementation : Proficient in translating advanced research into production-ready systems.

- Generative AI & LLMs : Hands-on with Transformer-based architectures and model development.

- Tech Stack : Expert in Python (OOP), ML libraries Scikit-learn, TensorFlow, PyTorch, Keras; solid grounding in data structures and algorithms.

- Core ML Algorithms : Mastery of Logistic/Linear Regression, Decision Trees, SVM, Gradient Descent, etc.

- Applied Tools : Experience with LangChain, LlamaIndex, and other LLM application frameworks.

- Statistical Foundations : Strong understanding of statistics and probability.

- Soft Skills : Excellent communicator and project manager capable of mentoring teams and presenting to clients and senior leadership.

- Advanced degree in Computer Science, Statistics, Mathematics, or related field.

- Prior products built using LLMs or generative AI systems.

- Familiarity with data governance, ethics, and compliance best practices.

- Experience with cloud platforms (AWS, Azure, etc.) or CRM systems applicable to Dataforce.