Data Scientist

ManpowerGroup; Milwaukee (WI); Hybrid; USD 120,000 - 160,000; Full time

Job summary

ManpowerGroup in Milwaukee is seeking a Data Scientist to join the North America Data & Analytics team. You will design and validate advanced analytics and ML solutions, translating business problems into actionable models, and partnering with IT and Data Engineering to prepare enterprise data.

Collaborate with cross-functional teams within the POD framework to move solutions through the AI lifecycle, ensuring governance, validation, and scalable production readiness.

Qualifications

• 3+ years of relevant experience in Data Science, ML, Applied Statistics, Operations Research, Advanced Analytics, or a closely related field.
• Proficiency in SQL and programming techniques and tools (Python, R); Cloud computing platforms: Azure, Snowflake; ML/AI: predictive modeling, classification, regression, clustering, feature engineering, experiment design, model validation, performance optimization; NLP: tokenization, sentiment analysis, embeddings; Collaboration with Data Eng, IT, Architecture, DevOps/MLOps, Product, and stakeholders in POD environments.
• Education: Bachelor's degree in Economics, Statistics, Mathematics, Computer Science, Data Science, Operations Research, or related quantitative field, or equivalent experience
• Nice to Have: Graduate degree in data science, statistics, or related field; Experience with Azure ML, MLflow, Azure DevOps; Experience with LLMs, Generative AI, embeddings; Experience producing model cards, audit-ready AI documentation

Responsibilities

• Design and validate advanced analytical and machine learning solutions for business impact.
• Translate business problems into predictive, prescriptive, optimization, and decision models.
• Define data requirements and create integration pipelines with Data Engineers.
• Lead model design activities: feature engineering, training, tuning, validation, performance optimization.
• Build predictive models with traceability, explainability, and trustworthiness.
• Apply responsible AI controls, eval criteria, bias/fairness checks, explainability, validation reporting.
• Create documentation supporting model design, validation, governance, and audit evidence
• Transform data science insights into scalable analytical products and decision-support capabilities
• Collaborate with cross-functional partners and communicate methods and limitations clearly
• Maintain lifecycle artifacts required by enterprise standards

Skills

SQL

Python

R

NLP

Machine Learning

Model Validation

MLOps

Embeddings

Education

Bachelor's degree in Economics, Statistics, Mathematics, Computer Science, Data Science, Operations Research, or related quantitative field

Tools

Azure ML

MLflow

Azure DevOps

Job description

Milwaukee-area Data Scientists, let's talk! We're looking for a talented Data Scientist to join our North America Data & Analytics team. Candidates located in or near Milwaukee who value collaboration, enterprise-scale impact, and a hybrid work environment at ManpowerGroup's headquarters are highly encouraged to apply. This is a unique opportunity to help shape the next generation of analytics and machine learning solutions for a global organization

The Data Scientist serves as a solution developer within the North America Regional Product-Oriented Delivery (POD) team, designing and validating advanced analytical and machine learning solutions that deepen understanding of the business, identify opportunities, and solve complex problems. The role translates business challenges into mathematical and statistical models, works with Data Engineering and IT partners to prepare enterprise data, and partners with Enterprise Technology AI Platform, MLOps, Architecture, Security, Compliance, and Operations teams to move governed solutions through the AI/ML lifecycle.

Making an Impact

• Design and create experimental analytical and machine learning solutions that quantify variable impacts on desired business outcomes using statistical, mathematical, and AI techniques.
• Translate complex business problems into predictive, prescriptive, optimization, and decision models that can be implemented, validated, and automated.
• Work with IT partners and Data Engineers to define data requirements and create integration and preparation pipelines that merge large structured and unstructured datasets for advanced analytics.
• Lead model design activities, including algorithm selection, feature engineering, experiment design, model training, hyperparameter tuning, testing, validation, and performance optimization.
• Design and build predictive models using principles that enhance traceability, reproducibility, relevance, explainability, and trustworthiness.
• Apply responsible AI controls, including documented evaluation criteria, robustness testing, bias and fairness assessment, explainability, and validation reporting.
• Create documentation supporting business justification, model design, validation, model cards, lineage, governance review, and audit evidence.

Sharing Expertise

• Proactively identify and frame critical, yet undefined, business problems as measurable analytical or AI use cases.
• Provide data science expertise to the North America Regional POD and clearly communicate analytical methods, assumptions, limitations, and recommendations.
• Develop reusable analytical assets, code, documentation, and practices that accelerate delivery and support consistent model quality.
• Transform data science insights into scalable analytical products and decision-support capabilities for business functions.

Gaining Exposure

• Collaborate with business leaders, product owners, Data Engineers, architects, and cross-functional partners of varying technical levels.
• Work within the Enterprise AI Industrialization framework with Enterprise Technology AI Platform, MLOps, DevOps, Security, Compliance, Architecture, Infrastructure, and Operations teams.
• Participate in solution architecture, governance, production-readiness, user acceptance testing, production validation, and post-deployment performance discussions.
• Translate complex findings and model results into a compelling narrative for non-technical stakeholders and decision makers.

Your Typical Day

• Partner with North America stakeholders to define AI and advanced analytics use cases, expected business value, success criteria, data needs, assumptions, and risks.
• Explore, prepare, and analyze large datasets; engineer features; design experiments; and program statistical, machine learning, and optimization models.
• Collaborate with Data Engineering and IT teams on approved data acquisition, integration, quality, preprocessing, metadata, and lineage requirements.
• Develop, test, validate, tune, and document models, including experiment results, performance thresholds, explainability, bias and fairness considerations, and model limitations.
• Partner with Enterprise Technology AI Platform and MLOps teams on environment readiness, versioning, CI/CD enablement, deployment requirements, monitoring configuration, and governed production promotion.
• Participate in user acceptance testing and production validation; review model performance, drift or degradation alerts, and retraining or issue-resolution needs with Operations and governance partners.
• Maintain model design documentation, validation reports, model cards, audit evidence, and other lifecycle artifacts required by enterprise standards.

Other accountabilities as assigned

Leverage and effectively use AI-enabled tools, technologies, and digital solutions, consistent with organizational policies and role requirements, to enhance effectiveness, efficiency, and decision-making. Apply appropriate human judgment, accountability, and ethical considerations in all technology-supported work in alignment with our Human First, Digital Always philosophy

Qualifications - External

Required

• 3+ years of relevant experience in Data Science, Machine Learning, Applied Statistics, Operations Research, Advanced Analytics, or a closely related field.
• Technical: Proficiency in SQL and programming techniques and tools (Python, R); Cloud computing platforms: Azure, Snowflake; Machine Learning and Advanced Analytics: predictive modeling, classification, regression, clustering, feature engineering, experiment design, model validation, and performance optimization; NLP skills including tokenization, sentiment analysis, and embeddings; Model Optimization: model tuning, hyperparameter adjustment, explainability, bias and fairness testing, reproducibility, monitoring, drift assessment, and model lifecycle management; Experience collaborating with Data Engineering, IT, Architecture, DevOps/MLOps, Product, and business stakeholders within Agile or Product-Oriented Delivery (POD) environments
• Education: Bachelor's degree in Economics, Statistics, Mathematics, Computer Science, Data Science, Operations Research, or related quantitative field, or equivalent experience

Nice to Have

• Graduate degree in data science, statistics, computer science, economics, operations research, or another quantitative field.
• Experience with Azure Machine Learning, MLflow, Azure DevOps, containerized deployment patterns, or model observability tooling.
• Experience with LLMs, Generative AI, embeddings, retrieval-augmented generation, or related evaluation practices.
• Experience producing model cards, algorithm validation reports, governance submissions, or audit-ready AI documentation.

ManpowerGroup is proud to be an equal opportunity affirmative action workplace. We celebrate diversity and are committed to providing an inclusive environment for all employees. Qualified applicants will receive consideration for employment without regard to race, religion, creed, color, national origin, citizenship, marital status, pregnancy (including childbirth, lactation and related medical conditions), age, gender, gender identity or expression, sexual orientation, protected veteran status, political ideology, ancestry, the presence of any physical, sensory, or mental disabilities, or other legally protected status.

A strong commitment is made by each employee and is necessary to ensure equal employment opportunity for all. ManpowerGroup is an inclusive workplace that will recruit, hire, train, and promote persons of all job titles, and ensure all other personnel actions are administered without regard to non-merit-based characteristics of individuals.

Reasonable accommodation during the interview process can be provided.