Pay
$154K–$225K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,958 postings in the last year. Stated ranges, not salaries paid.
Dearborn, MI, United States
Live, first seen by us 15 days agoWork setup in the employer’s posting: HybridFrom the employer’s posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Identify and prioritize Finance workflows to improve with data, analytics and AI
Recruit, mentor and develop a team of data scientists, AI engineers and software engineers
Lead the end-to-end lifecycle of AI/ML solutions, from prototype to monitoring
Set KPIs to measure the business impact of Finance data and AI initiatives
Present data and AI solutions to Finance executive leadership
Help Identify and prioritize key Finance workflows that can be enhanced with data, analytics and AI.
Recruit, mentor, and develop a high-performing team of data scientists, AI engineers, product managers and software engineers.
Lead the end-to-end lifecycle of AI/ML solutions, from ideation and prototyping to deployment, monitoring, and continuous improvement.
Establish key performance indicators (KPIs) and metrics to measure the effectiveness and business impact of data, analytics, and AI initiatives for Finance.
Present technical data, analytics and AI solutions to executive leadership within Finance in a clear and compelling manner.
Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.
10+ years of progressive experience in analytics, data science or AI roles.
6+ years of experience in a leadership role, building and managing high-performing data, analytics, and AI teams.
Experience supporting corporate finance functions such as FP&A, Accounting, Tax, Audit, Treasury.
Demonstrated expertise in statistical modeling, machine learning algorithms, generative AI and their practical application to business problems.
Master's degree or Ph.D. in a quantitative field.
Proficiency in programming languages commonly used in data science (e.g., Python, R, SQL).
Experience with (gen)AI/ML Ops practices and tools for deploying and managing production (gen)AI/ML tools at scale.
Demonstrated ability to influence and collaborate effectively with senior leadership and cross-functional teams, particularly within a matrixed organization like GDIA.
Basic Qualifications: - Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field. - 10+ years of progressive experience in analytics, data science or AI roles.
Preferred Qualifications: - Master's degree or Ph.D. in a quantitative field. - Proficiency in programming languages commonly used in data science (e.g., Python, R, SQL).
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$154K–$225K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,958 postings in the last year. Stated ranges, not salaries paid.
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- Master's degree or Ph.D. in a quantitative field. - Proficiency in programming languages commonly used in data science (e.g., Python, R, SQL). - Experience with (gen)AI/ML Ops practices and tools for deploying and managing production (gen)AI/ML tools at scale.
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We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
This leadership role is a critical part of the Global Data, Insights & Analytics (GDIA) team within Enterprise Technology, dedicated to supporting the Finance organization. You will be responsible for working closely with the Finance functions, in particular the Finance Operational Excellence (FOX) team that is leading the modernization and transformation strategy for Finance, all while aligning with GDIA's overarching data strategy and governance frameworks.
You will help define and execute the data and AI strategy specific to Finance, build and lead a world-class team, and work with the AI Advancement Center and Data Platform and Engineering teams as well as the ERP technology teams to establish the data infrastructure, governance, and AI capabilities necessary to support the FOX team’s transformation strategy. This role requires a strong technical leader with deep expertise in data science, AI, and a proven track record of delivering measurable business impact.
Basic Qualifications:
Preferred Qualifications:
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Dearborn, MI, United States
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