Senior Level Data Science Lead Jobs
Senior level data science lead jobs place experienced practitioners in charge of analytical strategy, model architecture decisions, and the cross-functional teams that turn data into measurable business outcomes. Openings concentrate across Biotechnology & Pharmaceuticals, Investment & Asset Management, and Insurance, with 50% remote or hybrid availability, and employers like UCB, Fidelity Investments, and AbbVie hiring at this level now.
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Prescient Edge is seeking a Data Science Lead to support a federal government client.
Please note that the availability of this position is contingent upon.
Benefits:
At Prescient Edge, we believe that acting with integrity and serving our employees is the key to everyone's success. To that end, we provide employees with a best-in-class benefits package that includes:
- A competitive salary with performance bonus opportunities.
- Comprehensive healthcare benefits, including medical, vision, dental, and orthodontia coverage.
- A substantial retirement plan with no vesting schedule. Career development opportunities, including on-the-job training, tuition reimbursement, and networking.
- A positive work environment where employees are respected, supported, and engaged.
Description:
- Oversee the development, deployment, and evaluation of predictive and prescriptive analytics to ensure alignment with mission objectives and operational needs.
- Establish a structured framework to distinguish data science and data engineering tasks, ensuring the effective allocation of resources and seamless collaboration between teams.
- Submit the Predictive Analytics Strategy & Implementation Report, detailing model development progress, algorithm validation, and mission integration.
- Coordinate to access compute and storage resources required to support large-scale model training and analytics workloads, including GPU accelerated environments, high-performance object storage, and parallel data processing capabilities.
- Fund usage-based compute and storage costs through inter-task chargeback arrangements, as approved by the Government PM.
Job Requirements:
Experience:
- Possess the knowledge and capability to lead the development of predictive and prescriptive analytics, ensuring alignment with mission objectives and the integration of AI/ML driven insights.
- Personnel must be proficient in advanced machine learning techniques, statistical modeling, and data science methodologies, with expertise in feature engineering, model validation, and data provenance tracking.
- Personnel must have experience implementing Agile methodologies, managing analytic sprints, and overseeing collaboration between data science and data engineering teams. Strong leadership, strategic planning, and stakeholder engagement skills are required to drive mission-focused analytic innovation.
- Personnel must have demonstrated experience in developing, deploying, and managing enterprise-level predictive analytics solutions, ensuring governance compliance, and implementing AI/ML models at scale.
- Experience in mission-focused analytics, data driven decision support, and integration of statistical and machine learning techniques is required.
- Personnel must have experience overseeing sprint-based Agile development cycles and working within cloud-based data science environments such as AWS, Azure, or Databricks.
Education:
- A Master’s degree in Data Science, Artificial Intelligence, Computer Science, or a related field, or eleven (11) years of equivalent experience in leading AI/ML-driven analytics programs.
- Desirable but not required certifications include AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate, or Certified Analytics Professional (CAP).
Security clearance:
- Active TS/SCI clearance.
Location:
- Doral, Florida. (USSOUTHCOM Headquarters)
Prescient Edge is seeking a Data Science Lead to support a federal government client.
Please note that the availability of this position is contingent upon.
Benefits:
At Prescient Edge, we believe that acting with integrity and serving our employees is the key to everyone's success. To that end, we provide employees with a best-in-class benefits package that includes:
- A competitive salary with performance bonus opportunities.
- Comprehensive healthcare benefits, including medical, vision, dental, and orthodontia coverage.
- A substantial retirement plan with no vesting schedule. Career development opportunities, including on-the-job training, tuition reimbursement, and networking.
- A positive work environment where employees are respected, supported, and engaged.
Description:
- Oversee the development, deployment, and evaluation of predictive and prescriptive analytics to ensure alignment with mission objectives and operational needs.
- Establish a structured framework to distinguish data science and data engineering tasks, ensuring the effective allocation of resources and seamless collaboration between teams.
- Submit the Predictive Analytics Strategy & Implementation Report, detailing model development progress, algorithm validation, and mission integration.
- Coordinate to access compute and storage resources required to support large-scale model training and analytics workloads, including GPU accelerated environments, high-performance object storage, and parallel data processing capabilities.
- Fund usage-based compute and storage costs through inter-task chargeback arrangements, as approved by the Government PM.
Job Requirements:
Experience:
- Possess the knowledge and capability to lead the development of predictive and prescriptive analytics, ensuring alignment with mission objectives and the integration of AI/ML driven insights.
- Personnel must be proficient in advanced machine learning techniques, statistical modeling, and data science methodologies, with expertise in feature engineering, model validation, and data provenance tracking.
- Personnel must have experience implementing Agile methodologies, managing analytic sprints, and overseeing collaboration between data science and data engineering teams. Strong leadership, strategic planning, and stakeholder engagement skills are required to drive mission-focused analytic innovation.
- Personnel must have demonstrated experience in developing, deploying, and managing enterprise-level predictive analytics solutions, ensuring governance compliance, and implementing AI/ML models at scale.
- Experience in mission-focused analytics, data driven decision support, and integration of statistical and machine learning techniques is required.
- Personnel must have experience overseeing sprint-based Agile development cycles and working within cloud-based data science environments such as AWS, Azure, or Databricks.
Education:
- A Master’s degree in Data Science, Artificial Intelligence, Computer Science, or a related field, or eleven (11) years of equivalent experience in leading AI/ML-driven analytics programs.
- Desirable but not required certifications include AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate, or Certified Analytics Professional (CAP).
Security clearance:
- Active TS/SCI clearance.
Location:
- Doral, Florida. (USSOUTHCOM Headquarters)
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Find JobsSenior Level Data Science Lead Job Market
Who's Hiring
- UCB2
- Fidelity Investments2
- AbbVie1
- DaVita1
- Klaviyo1
Top Industries Hiring
- Biotechnology & Pharmaceuticals3
- Investment & Asset Management2
- Insurance1
- Technology & Software1
- Healthcare & Medical Services1
Senior Level Data Science Lead Jobs: Frequently Asked Questions
How do I get a senior level data science lead job?
Employers at this level expect candidates to demonstrate ownership of end-to-end data science projects, not just technical execution. Highlight work where you defined the analytical approach, drove stakeholder alignment, and mentored junior data scientists. A portfolio showing business impact alongside model performance, combined with evidence of cross-functional leadership, gives you a clear edge over candidates with equivalent technical skills but narrower scope.
Which companies hire senior level data science leads?
Companies hiring senior level data science leads right now include UCB, Fidelity Investments, and AbbVie, based on current listings on Migrate Mate as of July 2026. Hiring at this level covers large enterprises with established data organizations, growth-stage technology companies scaling their analytics function, and consulting firms staffing embedded data science leadership for client engagements.
Are there remote senior level data science lead jobs?
Yes, remote and hybrid options are widely available at this experience level. About 50% of senior level data science lead openings are remote or hybrid as of July 2026, reflecting employer confidence in senior professionals who can lead distributed teams and communicate complex findings without daily in-person oversight. On-site roles tend to appear in highly regulated industries or where hands-on lab and data infrastructure access is required.
What makes a data science lead role senior level?
Senior level data science lead roles are defined by scope and accountability rather than task execution. You own the analytical roadmap for a product, business unit, or domain, make architectural decisions that affect the broader data stack, and mentor or manage data scientists whose output you are responsible for. Stakeholder influence, the ability to translate ambiguous business problems into data strategy, and a record of shipping work that changed decisions are the distinguishing factors.
Which industries hire the most senior level data science leads?
Senior Level data science lead roles concentrate in Biotechnology & Pharmaceuticals, Investment & Asset Management, and Insurance, based on current listings on Migrate Mate as of July 2026. These sectors drive hiring at this level because they operate at the scale and complexity where dedicated data science leadership, rather than individual contributors, is required to extract durable value from large, fast-moving datasets.