Senior Data Scientist

About the Role

• This role sits within our client's Technology organization, supporting a Data Science group focused on platform modernization initiatives. In this role, you will develop analytical prototypes and data science solutions in Python, working closely with both engineering teams and business stakeholders to turn ideas into production-ready tools.

• The work is split roughly 80% on assigned projects and business-driven initiatives, and 20% on research and development, exploring new technologies and innovative approaches.

Eligibility: Open to local candidates in DC, VA, or MD only. Candidates must be available for an in-person interview and complete a technical assessment.

What You'll Do:

* Design and build data science prototypes and analytical models in Python to support monitoring and detection use cases.

* Work with big data and open-source tools to explore and develop new analytical approaches.

* Create visualizations and dashboards (Plotly, Plotly Dash) that clearly communicate insights to business audiences.

* Translate complex analytical results into clear narratives and actionable recommendations for both technical and non-technical stakeholders.

* Partner with engineering teams to move prototypes and analytical work into production.

* Maintain high code quality and a production-oriented mindset throughout development.

Areas of Focus:

* Graph analytics

* Anomaly detection

* Signal processing

* Platform modernization initiatives

* Generative AI and agentic workflows (emerging focus)

What We're Looking For:

• Expert-level proficiency in Python.

• 8+ years of experience in data science or a related field.

• Hands-on experience with cloud infrastructure and the open-source data science ecosystem.

• Experience with visualization tools (Plotly, Plotly Dash).

• Familiarity with big data and enterprise data science platforms.

• Strong communication skills, with the ability to explain complex analytical work to technical and business audiences alike.

• A talent for storytelling with data, turning insights into cohesive, compelling narratives.

• Curiosity about the financial services domain (direct experience not required).

• Flexibility to adapt across evolving use cases and emerging technologies.

• A focus on building impactful, measurable solutions that can move into production.

Interview Process

Two rounds with a mix of data scientists and engineers, conducted in person.