Job Description:

The Role:

We are seeking an experienced and visionary Team Lead for our Data Science team. This is a hands-on leadership role, responsible for guiding a team of talented data scientists and ML engineers in developing and deploying advanced machine learning and AI solutions that drive decision-making for portfolio management, trading, and research functions. The ideal candidate combines deep technical expertise with servant leadership, strong collaboration skills, and a solid understanding of financial instruments and markets. Candidates with Master's or PhD degrees in quantitative fields are strongly preferred.

You will focus on

• Lead and mentor a high-performing data science team focused on building ML/AI solutions for investment, trading, and risk analytics
• Collaborate with researchers, traders, technologists, and portfolio managers to define and prioritize impactful data science projects
• Architect and oversee the development of models, natural language processing (NLP) tools, anomaly detection systems, and optimization algorithms
• Guide end-to-end model lifecycle: from data sourcing and feature engineering to model training, evaluation, deployment, and monitoring
• Foster a culture of continuous learning, innovation, and high accountability within the team
• Promote best practices in machine learning, reproducible research, and MLOps
• Drive strategic initiatives to improve data science infrastructure, tooling, and workflow automation

You will have

• Advanced degree (Master's or PhD) in Computer Science, Statistics, Applied Mathematics, Engineering, or a related field
• Deep expertise in machine learning, deep learning, NLP, and AI techniques
• Strong coding proficiency in Python, with familiarity with ML libraries such as Scikit-learn, TensorFlow, PyTorch, XGBoost and more.
• Solid understanding of financial instruments and investment workflows
• Excellent communication and stakeholder engagement skills
• Passion for leadership with a servant leadership mindset, focused on enabling team success
• Exposure to large-scale time series data, alternative data, or unstructured financial data
• Familiarity with cloud-based ML platforms (AWS SageMaker, Azure ML, etc.)

The Team

We are a data science team within the Quantitative Research and Investment Technology division in the Asset Management vertical. We partner with investment professionals, portfolio managers, analysts, quants, traders, and other technology teams to build AI/ML solutions that provide insight and drive measurable value. We focus on applied problems that can be taken from research to production. We enjoy learning new skills and have incorporated some LLM use cases into our pipeline, amongst other emerging technologies.

Certifications:

Category:

Fidelity's hybrid working model blends the best of both onsite and offsite work experiences. Working onsite is important for our business strategy and our culture. We also value the benefits that working offsite offers associates. Most hybrid roles require associates to work onsite every other week (all business days, M-F) in a Fidelity office.