Data Scientist 4

TSPi

$120K — $145K *
US-AnywhereRemote in United States
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's plus 9 years, Master's plus 7 years, or PhD plus 4 years of relevant experience.
  • Degree in data science, informatics, statistics, economics, social science, public health, or mathematics.
  • Strong understanding of AI tools, LLMs, and machine learning methodologies.
  • Experience managing analytics projects and client-facing deliverables.
  • Strong skills in SQL, Python, SAS, and/or R.
  • Proficient with version control tools like Git and Bitbucket.
  • Experience in consulting with direct client engagement.

Responsibilities

  • Implement AI, machine learning, and emerging analytical technologies for federal projects.
  • Lead AI monitoring and evaluation workflows.
  • Oversee analysis and visualization of federal datasets.
  • Manage delivery of analytical products and recommended insights for clients.
  • Provide leadership throughout the data lifecycle, from intake to analytics development.
  • Establish policies for effective data management and analytics.
  • Lead development of data quality and governance standards.

Benefits

  • Collaborative work environment with cross-functional teams.
  • Continuous improvement and innovation initiatives.
  • Opportunities for professional development and staying current with industry best practices.
  • Engagement in high-impact federal government projects.
  • Potential for involvement in cutting-edge AI and technology solutions.
Full Job Description
Opportunity

The successful candidate will support AI implementations in data-intensive federal government projects. Projects may include work involving social science, public health, natural resources, and other federal program data. This individual will be responsible for AI and data science solutioning and delivery, 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 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 support technical solution development, project planning, and implementation of advanced analytical methodologies that support client objectives and organizational growth.

Responsibilities
• Implement and promote the adoption and effective use of artificial intelligence, LLMs, machine learning, automation tools, and emerging analytical technologies.
• Lead the development of AI monitoring and evaluation workflows.
• 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 and analytics delivery.
• 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 planning, workload coordination, and delivery schedules to ensure successful project outcomes.
• 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 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 initiatives.

Required Skills / Experience
• 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.
• 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.
• Proficiency with version control tools including Git, Bitbucket, and SourceTree.
• Stay current on emerging trends, technologies, and best practices in data science, machine learning, and artificial intelligence and apply these learnings to project work.
• 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 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.

Preferred Skills / Experience
• Experience supporting federal data and research programs, particularly for NIH, USACE, NOAA or EPA contracts.
• PhD in a social science discipline.
• Experience with user research and human-centered design techniques applied to analytics programs.
• Experience evaluating and implementing AI-enabled processes, automation tools, and analytical efficiencies, including understanding the strengths and limitations of various AI LLMs.
• Proficiency with agile project management principles and tools, including Jira and Confluence.
• Experience developing reports and dashboards, reporting solutions, workflow automation, and integrated data products.
• Experience supporting data science, predictive analytics, machine learning, or AI-enabled products or initiatives.

Additional Information

Successful candidates are subject to a background investigation by the government and must be able to meet the requirements to hold a position of public trust.

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