Job Type: Direct Hire (Salaried)
Pay Range: $150,000 - $200,000
Location: Hybrid - Boston, MA (Minimum 3 days/week on-site)
About the Opportunity:
Our client, a leader in Financial Services, is looking for a skilled Principal Data Scientist to join their Distribution Enablement Group (DEG) in a permanent, salaried role. The core mission of the DEG is to drive business growth and improve efficiency by extracting insights from data and streamlining the use of data and technology. This role requires a technical and strategic leader to address business goals through data, automation, and AI. The project involves designing and delivering solutions that support distribution strategy and execution, including building analytic pipelines and powering initiatives such as client lead scoring for Sales. This is a high-impact role that requires a self-motivated professional who can hit the ground running and deliver results quickly.
Key Responsibilities & Deliverables:
This role is focused on the successful completion of specific tasks and deliverables. Your responsibilities will include:
- Partnering with Sales, Marketing, Finance, and other Business teams to understand their requirements and translate their goals into scalable data solutions and automated workflows.
- Developing, deploying, and maintaining data and analytics pipelines that support business objectives, analytic processes, and interactive dashboards.
- Partnering with IT to deliver on Business objectives, including production code deployments, data collection & integration, front-end user experience, and back-end infrastructure.
- Contributing to technical architecture, documentation, and governance related to data, automation, and AI, and supporting the incorporation and responsible use of AI across Business workflows.
- Monitoring, troubleshooting, and optimizing analytic and data processes to ensure reliability, performance, and availability.
We are looking for someone with a proven track record of successful engagements. The ideal candidate will have:
- 7+ years of experience in data science, analytics engineering, or a related role, preferably within financial services or another highly regulated industry.
- Deep expertise in Python and SQL, and demonstrated experience implementing machine learning solutions (model development, deployment, and ongoing monitoring in production environments). This isn't a learning role—you need to be a subject matter expert.
- Strong proficiency using Git for version control and collaboration, along with a solid understanding of machine learning techniques, statistical analysis, and data modeling concepts.
- Experience leveraging cloud platforms or remote compute environments to support data processing and analytics workloads.
- Strong written and verbal communication skills, with the ability to translate complex technical concepts for non-technical stakeholders, and a proven ability to manage multiple priorities.
