Data Science Manager

Gilbane Building Company•Tampa, FL

33d•$180,000 - $210,000

About The Position

Gilbane is seeking a Data Science Manager to lead a team responsible for applying advanced analytics, statistics, machine learning, causal inference, and artificial intelligence (AI) to solve complex business problems and improve outcomes. This role combines technical leadership, people management, stakeholder partnership, and solution delivery to move models, insights, and AI-enabled capabilities into production and adoption. This leader helps the organization understand business drivers, predict outcomes, identify opportunities, and translate complex analytical concepts into clear, actionable recommendations. Gilbane is a family-owned business with 45 offices that has been shaping communities since 1870. As a Top-10 ENR Contractor, Gilbane is consistently recognized as one of the most reputable construction management firms in the country and is committed to delivering projects safely and on-time. You will have the opportunity to build schools, labs, hospitals, corporate offices, sports arenas and more! We are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.

Requirements

Bachelor's degree required; master's degree required in statistics, data science, economics, psychology (industrial/organizational, research, or experimental focus), biometrics, or another heavily quantitative field; applied science preferred
5 years of experience as a Data Scientist
2+ years of people management experience leading data scientists, analysts, applied scientists, or quantitative researchers
Or equivalent combination of education and experience
Deep knowledge of statistical analysis, predictive modeling, machine learning, data mining, feature engineering, causal inference, and scientific research methods
Strong technical proficiency in industry standard data science and analytics tools and programming languages
Demonstrated experience applying analytics, AI, machine learning, and causal inference to real business problems from discovery through implementation and adoption
Strong communication, consultative, and presentation skills, with the ability to explain complex methods and model outputs to non-technical audiences
Proven ability to partner with business stakeholders, technical teams, and subject matter experts
Experience deploying machine learning or AI solutions into production with engineering, Business Intelligence (BI), or technology teams
Experience building data science operating models, delivery standards, model governance, reusable analytical frameworks, or process changes based on analytical findings
Applicants must be authorized to work in the United States without current or future sponsorship.

Nice To Haves

PhD preferred

Responsibilities

Leads, coaches, and develops data scientists through technical direction, career guidance, performance feedback, and professional growth support
Sets standards for analytical quality, experimentation, causal inference, machine learning, AI solution design, model documentation, reproducibility, validation, and responsible AI use
Guides the team in applying statistical analysis, predictive modeling, feature engineering, data mining, and scientific research methods to solve business problems
Reviews analytical approaches, model assumptions, feature development, variable importance, and results interpretation to ensure outputs are reliable, explainable, and actionable
Prioritizes the portfolio based on business value, feasibility, stakeholder readiness, data quality, and strategic alignment
Builds trusted relationships with business leaders, subject matter experts, Data Engineering, Business Intelligence (BI), and Information Technology (IT)
Translates ambiguous business questions into well-scoped analytical problems, hypotheses, measurable outcomes, and executable plans
Educates stakeholders and partners with business subject matter experts (SMEs) to share knowledge on analytics, AI, and machine learning processes, validate findings, improve adoption, and influence process changes based on analytical recommendations
Communicates insights, recommendations, risks, tradeoffs, and opportunities to executive and non-technical audiences through clear storytelling, presentations, and documentation
Responsible for the career development and coaching of team members
Fosters a positive and inclusive work environment to motivate and engage team members
Interprets and translates the organizational strategy, ensuring team understanding of their role in accomplishing strategic goals