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Overnight Python Data Science Jobs in Wisconsin (NOW HIRING)

Deloitte

Lead AI and Data Science Engineer II

Milwaukee, WI · On-site

$101K - $133K/yr

Experience using Python and Structured Query Language (SQL), with working knowledge of JavaScript ... Lead AI and Data Science Engineer II Drive the design and delivery of advanced analytics ...

MSCCN

Senior Data Scientist - Madison WI

Mcfarland, WI · On-site

$100K/yr

... data science projects 3+ yrs of coding experience in Python Understanding of biopharmaceuticals process and related unit operations Experience using Git for version control Familiarity with DevOps ...

Tiger Analytics, LLC

WI · On-site

$130 - $160/hr

Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted ... Strong programming skills in Python- Production level coding and SQL. * Experience working with ...

LexisNexis Risk Solutions

WI · On-site

$115.40 - $192.30/hr

Proficient user of Python, SQL, Pandas, and NumPy.* Competent user of Java.* Demonstrates proficiencies in Data Science and Machine Learning frameworks. Experience with Generative AI, OpenAI, Copilot ...

Merkle Science

WI · On-site

$100 - $130/hr

Merkle Science is looking for a data scientist to develop and implement clustering and attribution heuristics for on-chain cryptocurrency data. This role requires expertise in Python and SQL, and ...

Rivi Consulting Group

Java Software emgineer

Green Bay, WI · On-site

$50.25 - $69/hr

Proficiency with Python data science libraries (Pandas, NumPy, Scikit-learn). * Experience with data visualization tools and techniques. * Understanding of optimization algorithms (linear programming ...

Fiserv, Inc.

Sr Data Scientist

Milwaukee, WI · On-site

Bachelor's degree in Statistics, Data Science, Computer Science, Operations Research or a related ... with Python programming language; 4 years deploying, monitoring, and maintaining ML/DL model ...

Jobtailor

WI · On-site

$120 - $180/hr

... the data science discipline * Choose best fit methods, define algorithms, validate, and deploy ... C, C++, Java, Python, Scala (preferred) * Experience with statistical software and database ...

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Overnight Python Data Science information

What is an overnight Python data science job?

Overnight Python Data Science jobs involve working night shifts to perform data analysis, build models, or process data using Python programming. These roles may include tasks like cleaning datasets, running automated pipelines, and generating reports for teams that operate on a 24-hour cycle. Such positions are common in industries that require round-the-clock data monitoring or support, such as finance, healthcare, or IT operations. Professionals in these roles typically have experience with Python, data science libraries, and may collaborate with global teams across different time zones.

What are the main challenges of working as an overnight Python data science professional, and how can I succeed in this role?

Working as an Overnight Python Data Science professional often means handling data pipelines, model monitoring, and urgent troubleshooting during hours with limited team support. The main challenges include quickly resolving unexpected data issues, maintaining high attention to detail during late hours, and communicating findings to daytime teams. Success in this role relies on strong problem-solving skills, proactive communication (such as clear shift handovers), and the ability to work independently while following established protocols. Building robust documentation and automating regular tasks can also help manage workload and reduce errors.

How much does an Overnight Python Data Science professional make?

An overnight Python Data Science professional typically earns between $70,000 and $120,000 annually, depending on experience, location, and industry. Salaries may be higher for those with advanced skills in machine learning, big data tools, and relevant certifications, especially for roles requiring overnight or shift work.

What skills and qualifications are needed to thrive as an overnight Python data science professional?

To thrive as an Overnight Python Data Science professional, you need strong analytical skills, proficiency in Python programming, and a solid understanding of statistics and machine learning concepts, often backed by a degree in a quantitative field. Familiarity with tools such as Jupyter Notebook, Pandas, Scikit-learn, and data visualization libraries, along with experience using databases and cloud platforms, is typically required. Excellent problem-solving skills, attention to detail, and the ability to work independently during non-standard hours help you excel in this role. These skills and qualities are vital for efficiently analyzing data, building reliable models, and delivering actionable insights in a time-sensitive, often autonomous overnight environment.

What is the difference between Overnight Python Data Science vs Data Analyst?

AspectOvernight Python Data ScienceData Analyst
Required SkillsPython, data analysis, machine learning, statistical modelingExcel, SQL, data visualization, basic statistics
Work EnvironmentRemote or night shifts, tech-focused companies, data-driven rolesOffice-based or remote, business or marketing departments
Industry UsageTech, finance, e-commerce, healthcareRetail, finance, marketing, consulting

Overnight Python Data Science roles focus on advanced data analysis, machine learning, and programming skills, often requiring night shifts and remote work. Data Analysts typically handle data visualization, reporting, and basic analysis during regular hours. Both roles are essential in data-driven industries but differ in technical complexity and work schedules.

What are the most commonly searched types of Python Data Science jobs in Wisconsin? The most popular types of Python Data Science jobs in Wisconsin are:
Overnight Python Data Science jobs near you

Lead AI and Data Science Engineer II

Deloitte

Milwaukee, WI • On-site

$101K - $133K/yr

Full-time

Posted 13 days ago

Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services

Job description

Lead AI and Data Science Engineer II

Drive the design and delivery of advanced analytics, artificial intelligence (AI), and generative artificial intelligence (GenAI) solutions that inform Talent strategy and workforce decisions. In this role, you will lead complex data science work that combines research design, statistical analysis, machine learning, and application development to solve high-priority people challenges. You will also partner with business, Talent, and technology stakeholders to translate workforce data into actionable insights, tools, and recommendations.

Recruiting for this role ends on August 10, 2026.

Work You'll Do

In this role, you will lead the data science dimension of that work, shaping research design, analytical methodology, and solution development while helping develop junior data scientists across the full analytics lifecycle.

Strategy & Stakeholder Partnership

  • Partner with the Advanced Analytics & AI leader to help shape and execute the People Analytics portfolio, using data-driven insights to inform Talent strategy, establish priorities, and manage multiple initiatives.
  • Collaborate with stakeholders across Talent, business leadership, and ITS to define business needs, identify analytics opportunities, communicate complex technical concepts, and advise on the benefits and limitations of automation and artificial intelligence (AI).
  • Develop and drive strategy to understand and improve data quality across relevant Talent data assets.

Analytics & Data Science

  • Design and structure analytical work, including research design, project planning, and use case development, and apply advanced statistical and machine learning methods to generate rigorous, actionable insights.
  • Perform analytics in cloud-based environments, support the development of clear leadership-ready presentations, and stay current on developments in data science, behavioral science, and adjacent disciplines.

Software & Data Engineering

  • Develop full-stack, web-based data and generative artificial intelligence (GenAI) applications that improve Talent reporting and business operations.
  • Partner with data engineering teams on pipeline architecture and infrastructure, using knowledge of extract, transform, load (ETL), version control, and continuous integration and continuous delivery (CI/CD) concepts to inform technical decisions.

People Leadership

  • Mentor junior and mid-level data scientists across the analytics lifecycle, from problem framing and data collection through analysis and synthesis of findings.
  • Provide structure and oversight for analytically complex projects, while assessing talent, delivering developmental feedback, and contributing to a high-performing analytics team.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

The Talent Experience & Engagement, People Analytics - Advanced Analytics & AI team helps the firm make informed people and business decisions by translating workforce data into actionable insights, tools, and strategies. The team combines behavioral science, organizational research, advanced analytics, and artificial intelligence (AI) to address leadership questions, improve decision-making, and create scalable solutions with measurable impact.

The work is delivered through two connected capabilities. Organizational research and storytelling ground analyses in rigorous social science and clear, decision-oriented narratives. Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns in workforce data, build data and generative artificial intelligence (GenAI) applications, and partner with Talent data engineering teams on pipelines and infrastructure.

Qualifications

Required:

  • Graduate degree in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • 6+ years of experience in data science, analytics, or applied research
  • Experience using Python and Structured Query Language (SQL), with working knowledge of JavaScript, TypeScript, HyperText Markup Language (HTML), and Cascading Style Sheets (CSS)
  • Experience applying multivariate statistics and machine learning methods, including regression, structural equation modeling, factor analysis, decision trees, clustering, and dimension reduction, in Apache Spark or Databricks environments
  • Experience developing artificial intelligence (AI) or generative artificial intelligence (GenAI) applications and working with extract, transform, load (ETL), pipeline design, and orchestration concepts
  • Demonstrated experience leading AI strategy and enabling adoption of AI or data engineering tools within a complex organizational environment
  • Mentorship of junior and mid-level analysts, providing guidance across the analytics lifecycle from conception through data mining/analysis and synthesis of results
  • Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred:

  • Doctor of Philosophy (PhD) in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • Experience in a professional services organization or large matrixed organization
  • Experience designing and building end-to-end data pipelines for reporting and analytics
  • Experience applying behavioral science frameworks to interpret workforce data and generate insight - not solely technical or statistical proficiency
  • Experience with talent systems such as OneModel or SAP

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $118700 to $218600.

Qualifications:

Lead AI and Data Science Engineer II

Drive the design and delivery of advanced analytics, artificial intelligence (AI), and generative artificial intelligence (GenAI) solutions that inform Talent strategy and workforce decisions. In this role, you will lead complex data science work that combines research design, statistical analysis, machine learning, and application development to solve high-priority people challenges. You will also partner with business, Talent, and technology stakeholders to translate workforce data into actionable insights, tools, and recommendations.

Recruiting for this role ends on August 10, 2026.

Work You'll Do

In this role, you will lead the data science dimension of that work, shaping research design, analytical methodology, and solution development while helping develop junior data scientists across the full analytics lifecycle.

Strategy & Stakeholder Partnership

  • Partner with the Advanced Analytics & AI leader to help shape and execute the People Analytics portfolio, using data-driven insights to inform Talent strategy, establish priorities, and manage multiple initiatives.
  • Collaborate with stakeholders across Talent, business leadership, and ITS to define business needs, identify analytics opportunities, communicate complex technical concepts, and advise on the benefits and limitations of automation and artificial intelligence (AI).
  • Develop and drive strategy to understand and improve data quality across relevant Talent data assets.

Analytics & Data Science

  • Design and structure analytical work, including research design, project planning, and use case development, and apply advanced statistical and machine learning methods to generate rigorous, actionable insights.
  • Perform analytics in cloud-based environments, support the development of clear leadership-ready presentations, and stay current on developments in data science, behavioral science, and adjacent disciplines.

Software & Data Engineering

  • Develop full-stack, web-based data and generative artificial intelligence (GenAI) applications that improve Talent reporting and business operations.
  • Partner with data engineering teams on pipeline architecture and infrastructure, using knowledge of extract, transform, load (ETL), version control, and continuous integration and continuous delivery (CI/CD) concepts to inform technical decisions.

People Leadership

  • Mentor junior and mid-level data scientists across the analytics lifecycle, from problem framing and data collection through analysis and synthesis of findings.
  • Provide structure and oversight for analytically complex projects, while assessing talent, delivering developmental feedback, and contributing to a high-performing analytics team.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

The Talent Experience & Engagement, People Analytics - Advanced Analytics & AI team helps the firm make informed people and business decisions by translating workforce data into actionable insights, tools, and strategies. The team combines behavioral science, organizational research, advanced analytics, and artificial intelligence (AI) to address leadership questions, improve decision-making, and create scalable solutions with measurable impact.

The work is delivered through two connected capabilities. Organizational research and storytelling ground analyses in rigorous social science and clear, decision-oriented narratives. Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns in workforce data, build data and generative artificial intelligence (GenAI) applications, and partner with Talent data engineering teams on pipelines and infrastructure.

Qualifications

Required:

  • Graduate degree in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • 6+ years of experience in data science, analytics, or applied research
  • Experience using Python and Structured Query Language (SQL), with working knowledge of JavaScript, TypeScript, HyperText Markup Language (HTML), and Cascading Style Sheets (CSS)
  • Experience applying multivariate statistics and machine learning methods, including regression, structural equation modeling, factor analysis, decision trees, clustering, and dimension reduction, in Apache Spark or Databricks environments
  • Experience developing artificial intelligence (AI) or generative artificial intelligence (GenAI) applications and working with extract, transform, load (ETL), pipeline design, and orchestration concepts
  • Demonstrated experience leading AI strategy and enabling adoption of AI or data engineering tools within a complex organizational environment
  • Mentorship of junior and mid-level analysts, providing guidance across the analytics lifecycle from conception through data mining/analysis and synthesis of results
  • Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred:

  • Doctor of Philosophy (PhD) in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • Experience in a professional services organization or large matrixed organization
  • Experience designing and building end-to-end data pipelines for reporting and analytics
  • Experience applying behavioral science frameworks to interpret workforce data and generate insight - not solely technical or statistical proficiency
  • Experience with talent systems such as OneModel or SAP

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to ski...

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