Senior Principal Data Scientist

Role Overview

As a Senior Principal Data Scientist, you will play a pivotal role in redefining how the Company leverages data science to achieve its mission. This role requires a strategic leader who can translate complex business objectives into actionable analytical solutions, collaborate with cross-functional teams, and deliver hands-on contributions to high-priority projects. You will work closely with company leadership, internal data scientists, and data engineering teams to shape cutting-edge technology and analytics capabilities, while mentoring and elevating team expertise to establish a center of excellence.

Key Responsibilities

• Strategic Partnership: Engage with company leadership and stakeholders to understand business objectives, clarify ambiguous requirements, and translate desired outcomes into robust data science solutions.
• Solution Design: Architect and implement advanced analytical models, leveraging new technology capabilities to address complex challenges and drive measurable impact.
• Hands-On Execution: Lead and contribute directly to high-priority data science projects, including predictive modeling, machine learning, and statistical analysis, in a bandwidth-constrained environment.
• Cross-Functional Collaboration: Partner with data engineering and internal data science teams to ensure seamless integration of data pipelines, tools, and models into production environments.
• Stakeholder Enablement: Educate and empower stakeholders with limited data science exposure, helping them articulate needs and understand the potential of advanced analytics.
• Center of Excellence Development: Drive the long-term vision for a data science center of excellence by establishing best practices, mentoring junior data scientists, and fostering a culture of innovation and technical rigor.
• Tooling & Process Improvement: Identify and implement improvements to data science tooling, workflows, and processes to overcome historical underinvestment and enhance team efficiency.

Qualifications

• Education: Advanced degree (Ph.D. or Master’s) in Data Science, Statistics, Computer Science, Mathematics, or a related field.

Experience:

• 8+ years of experience in data science, with at least 3 years in a senior or principal role leading complex, high-impact projects.
• Proven track record of translating ambiguous business needs into successful data science solutions in a stakeholder-facing role.
• Extensive hands-on experience with advanced analytics, including machine learning, statistical modeling, and big data frameworks (e.g., Python, R, TensorFlow, PyTorch, Spark).
• Experience collaborating with data engineering teams to deploy models and integrate with modern data platforms.
• Prior work in highly regulated or complex industries is a plus but not required.

Technical Skills:

• Proficiency in programming (Python, R, SQL) and data science libraries (e.g., pandas, scikit-learn, NumPy).
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and modern data engineering tools (e.g., Airflow, Databricks).
• Strong understanding of data visualization and storytelling tools (e.g., Tableau, Power BI) to communicate insights effectively.

Soft Skills:

• Exceptional communication skills, with the ability to distill complex technical concepts for non-technical stakeholders.
• Strategic mindset with a talent for identifying opportunities and driving organizational change.
• Collaborative team player comfortable mentoring others and thriving in a fast-paced, resource-constrained environment.

Leadership: Demonstrated ability to lead cross-functional initiatives, mentor junior team members, and build organizational capability in data science.