Principal Data Scientist

Fidelity Investments • Boston, MA

10d • Hybrid

About The Position

Within Fidelity’s Enterprise Technology Artificial Intelligence Center of Excellence (ET AI CoE), you will help shape the next generation of AI at Fidelity, designing and building critical AI capabilities and services that will benefit institutional and retail clients for years to come. You’ll engage directly with business partners to navigate the complexities of artificial intelligence, advanced analytics, and machine learning, delivering scalable, production-ready solutions that drive customer and business value. As a Principal Data Scientist, you will be a hands-on technical leader and mentor, guiding standard processes across NLP, speech analytics, and generative AI model development. You’ll join a team passionate about innovation, working with modern cloud and open-source technologies while solving some of the financial industry’s most exciting data challenges. The Team Our AI team propels Fidelity forward by researching, developing, and scaling sophisticated AI algorithms, models, frameworks, platforms, and technologies that transform customer experiences and drive measurable business outcomes. As a Principal Data Scientist, you will play a vital technical leadership role: mentoring and uplifting other engineers, building collaborative partnerships, and setting the tone for quality and innovation. Our diverse group draws on multidisciplinary strengths: Data Science, ML engineering, software, and domain expertise to continually advance Fidelity’s position at the forefront of applied AI. The Value You Deliver You will be a trusted AI partner helping business, product, and engineering partners translate business requirements into real-world next-generation AI-driven solutions. The ideal candidate combines expert open-source AI/ML modeling with hands-on technical experience to build algorithms, models and, occasionally, applications that surface insights and deliver value (revenue and/or cost saving benefits, customer experiences/journeys, and increased efficiencies through automation/optimization).

Requirements

• Advanced degree or equivalent experience (Master’s or PhD) in Computer Science, Machine Learning, Data Science, Engineering, or a related field, or equivalent practical experience.
• Experience designing, building, and deploying AI/ML models in production environments, with deep understanding of MLOps standards (scalable architectures, reproducibility, monitoring, CI/CD, and compliance).
• Extensive hands-on expertise with: Natural Language Processing (NLP) and computational linguistics, including entity recognition, text summarization, and conversational analytics.
• Programming in Python (primary), with experience in modern ML libraries (PyTorch, transformers, etc.).
• Cloud-based workflows (AWS SageMaker, Bedrock, Athena, Snowflake).
• RAG pipelines for retrieval-augmented generation, enabling context-aware responses and integration of external knowledge sources.
• Demonstrated technical leadership: mentoring and upskilling data scientists, conducting peer code/design reviews, driving architectural decisions, and championing engineering excellence.
• Ability to communicate complex technical topics clearly and persuasively to both technical and non-technical partners (including strong technical writing/documentation skills).
• Ability to decompose research or tactical deliverables into modular, reusable, strategic capabilities/services.
• Excellent communication and presentation skills while being comfortable collaborating in team settings.

Nice To Haves

• Experience working with audio data pipelines, speech recognition (ASR), audio-to-audio processing, and conversational AI (including dialogue systems, call transcription, or voice assistants).
• Experience with modern real-time and streaming data technologies (such as Apache Kafka, AWS Kinesis, Apache Pulsar, or cloud-native event streaming platforms).
• Hands-on CUDA/GPU optimization experience for accelerating AI/ML workloads.

Responsibilities

• Designing and building critical AI capabilities and services
• Delivering scalable, production-ready solutions that drive customer and business value
• Guiding standard processes across NLP, speech analytics, and generative AI model development
• Mentoring and uplifting other engineers
• Building collaborative partnerships
• Setting the tone for quality and innovation
• Helping business, product, and engineering partners translate business requirements into real-world next-generation AI-driven solutions
• Building algorithms, models and, occasionally, applications that surface insights and deliver value

Benefits

• comprehensive health care coverage and emotional well-being support
• market-leading retirement
• generous paid time off and parental leave
• charitable giving employee match program
• educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level