Data Scientist Manager

TSP LLC• US,

1d•$110,000 - $175,000

About The Position

TSPi is seeking a Data Scientist Manager with experience leading teams supporting federal data science and analytics programs. TSPi excels in meeting the needs of our partners (clients) by offering advanced technology solutions utilizing our industry-specific knowledge, iterative Agile approach, commitment and passion to serve, collaborative and fun team atmosphere, and pride in our work. The successful candidate will lead teams of data scientists, data analysts, and other technical staff supporting data-intensive federal government projects. Projects may include work involving healthcare, social science, public health, and other federal program data. This individual will be responsible for managing analytics delivery, overseeing data management, data science, and analytical activities, supporting client engagements, and ensuring the production of high-quality data products and actionable insights. The ideal candidate combines strong technical expertise in data analytics and data science with demonstrated experience leading project teams, managing project execution, and embracing emerging technologies, including artificial intelligence and machine learning capabilities, to improve analytical outcomes and operational efficiency. The candidate will also be responsible for managing a team of data scientists, analysts, and engineers administratively and engaging in one-on-one meetings to provide mentorship, monitor performance and utilization, and nurture career growth. They will also be responsible for recruitment efforts to expand the overall data science and analytics team to support business growth.

Requirements

Bachelor's degree plus 9 years of relevant experience, Master's degree plus 7 years of relevant experience, or PhD plus 4 years of relevant experience.
Degree in a data-focused discipline such as informatics, statistics, data science, computer science, economics, social science, public health, mathematics, or a related field.
Strong understanding of AI tools and LLMs, machine learning concepts, analytical methodologies, and emerging technologies relevant to data analytics and data science.
Demonstrated experience leading and managing teams of data analysts, data scientists, data engineers, and other technical professionals.
Experience managing analytics projects, contract tasks, and client-facing deliverables.
Strong expertise in statistical, data analytics, and data management languages including SQL, Python, SAS, and/or R.
Strong experience with cloud platforms including AWS, Azure, or GCP.
Experience working with relational databases and modern data management platforms including Databricks and Snowflake as well as with associated technologies including Docker, Kubernetes, MLFlow, or similar platforms.
Experience implementing data governance, QA/QC, and data lifecycle management practices.
Stay current on emerging trends, technologies, and best practices in data science, machine learning, and artificial intelligence and apply these learnings to project work and employee mentorship.
Experience evaluating and implementing AI-enabled processes, automation tools, and analytical efficiencies including understanding the pros and cons of various AI LLMs.
Experience working in a consulting environment, including direct client engagement and stakeholder communication.
Strong technical writing skills with the ability to produce clear, concise, and well-documented analyses, reports, and presentations.
Critical thinker with strong leadership, communication, collaboration, and problem-solving skills.
Experience supporting proposal efforts, technical solutioning, and business development activities.
Ability to obtain and maintain public trust access for federal information systems and successfully complete a federal background check.

Nice To Haves

Experience managing federal data and analytics programs particularly for CMS contracts.
Experience with data linking methodologies, including fuzzy matching techniques such as Levenshtein distance, Jaccard similarity index, and Jaro-Winkler similarity index.
Proficiency with version control tools including Git, Bitbucket, and SourceTree.
Proficiency with agile project management principles and tools, including Jira and Confluence.
Experience with leading analytic code translation and modernization efforts from SAS to Python including code evaluation and refactoring.
Experience developing reports and dashboards, reporting solutions, workflow automation, and integrated data products.
Experience supporting data science, predictive analytics, machine learning, or AI-enabled initiatives.
Experience managing multidisciplinary teams in Agile project environments.

Responsibilities

Implement and promote the adoption and effective use of artificial intelligence, LLMs, machine learning, automation tools, and emerging analytical technologies.
Oversee the analysis, visualization, and interpretation of various federal datasets.
Manage delivery of analytical products, reports, dashboards, and data-driven recommendations to clients and stakeholders.
Provide leadership across the data lifecycle, including data intake, storage, governance, synthesis, automation, and analytical development.
Establish and implement policies, processes, and procedures that support effective data management, analytics delivery, and team performance.
Lead the development and implementation of QA/QC protocols, defect tracking processes, and data governance standards to ensure data quality, integrity, security, and availability.
Serve as the primary technical and operational point of contact for clients, stakeholders, and project leadership.
Manage project priorities, resource allocation, staffing, workload balancing, and delivery schedules to ensure successful project outcomes.
Lead and manage teams of data analysts, data scientists, data engineers, and other technical staff across multiple projects and workstreams.
Mentor, coach, and develop team members, providing technical guidance, performance feedback, and career development support.
Evaluate AI-enabled tools and methodologies to improve data processing, coding efficiency, workflow automation, and analytical capabilities.
Support proposal development, technical solutioning, project planning, and business development activities.
Collaborate with cross-functional teams including project leadership to communicate insights and translate complex analytical findings into actionable recommendations.
Promote continuous improvement, innovation, and adoption of industry best practices across analytics and data science teams.