1

Data Science Jobs in Racine, WI (NOW HIRING)

Senior AI Engineer - SFL Scientific

Milwaukee, WI · On-site

$103K - $141K/yr

Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on ...

MLOps Engineer II (Remote)

Menomonee Falls, WI · On-site

$97K - $134K/yr

Collaborate with Data Scientists and Engineers across the full ML lifecycle, including building and scaling ETL pipelines, deploying models into customer-facing applications, and enabling efficient ...

... Data Science, and Data Governance - Architecting and implementing cloud-based solutions meeting industry standards Travel Requirements Up to 60% Job Posting End Date The salary range for this ...

It is expected that this individual continuously invests in learning and stays informed of the latest in Data Governance, Analytics, and Data Science approaches, solutions, frameworks, technology ...

Collaborate with Data Science team to improve data collection/usage across sources. * Explore tools in partnership with Data Science team to improve research efficiency. * Identify and promote ...

Showing results 41-60

Data Science information

See Racine, WI salary details

$35.2K

$115.1K

$184.3K

How much do data science jobs pay per year?

As of Jul 25, 2026, the average yearly pay for data science in Racine, WI is $115,089.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,400.00 and $127,500.00 per year, depending on experience, location, and employer.

Is data science a good career?

Data science is a growing field with high demand for professionals skilled in statistics, programming, and data analysis tools like Python and R. It offers competitive salaries, diverse industry applications, and opportunities for advancement, making it a strong career choice for those with relevant skills and education.

What are the key skills and qualifications needed to thrive as a Data Scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What jobs can a Data Scientist do?

A Data Scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What work do you do as a Data Scientist?

A Data Scientist analyzes large datasets to extract insights, build predictive models, and inform business decisions. They use programming languages like Python or R, and tools such as SQL and machine learning frameworks, often working in collaborative environments with data engineers and analysts.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
What are the most commonly searched types of Data Science jobs in Racine, WI? The most popular types of Data Science jobs in Racine, WI are:
What are popular job titles related to Data Science jobs in Racine, WI? For Data Science jobs in Racine, WI, the most frequently searched job titles are:
What cities near Racine, WI are hiring for Data Science jobs? Cities near Racine, WI with the most Data Science job openings:
Infographic showing various Data Science job openings in Racine, WI as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $115,089 per year, or $55.3 per hour.
NM Capital - Investment Data Analyst

NM Capital - Investment Data Analyst

Northwestern Mutual Life Insurance Company

Milwaukee, WI • On-site

$86K - $130K/yr

Full-time

Posted 10 days ago


Northwestern Mutual rating

8.0

Company rating: 8.0 out of 10

Based on 73 frontline employees who took The Breakroom Quiz

147th of 281 rated insurance


Job description

About the Job:

  • This role will focus on the data associated with NMC's investment transaction lifecycle; including deal sourcing, due diligence, valuation, portfolio monitoring, portfolio performance, and reporting to clients.
  • Manage, transform, and integrate portfolio and benchmark data to support advanced quantitative analysis, ensuring information is accurate, auditable, and analytically robust.
  • Develop and maintain investment performance measurement frameworks, including returns, benchmarks, attribution, and performance drivers at the asset, strategy, and portfolio level.
  • Design and deliver custom analyses and models to answer adhoc investment, portfolio management, and investor questions.
  • Identify, define, and refine key investment metrics and analytical views that inform investment decisions and support positive business outcomes.
  • Build and maintain Power BI dashboards that combine quantitative outputs and visual storytelling to support portfolio management and senior leadership.
  • Partner with investment, finance, and investor relations teams to support due diligence, investor requests, marketing materials, and quarterly performance reporting.
  • Engage users with analytically rigorous tools and datasets, creating a virtuous cycle where insights drive adoption and improved data quality.
  • Configure eFront and assist users with troubleshooting and best practices.
  • Contribute to the design and maintenance of AIready datasets by optimizing and enhancing datasets for consumption by investment professionals.
  • Clearly document analytical methodologies, assumptions, data standards, and repeatable processes.

What You'll Bring to the Role:

  • Bachelor's and/or master's degree in Finance, Economics, Statistics, Data Science, Computer Science, Financial Engineering, or a related quantitative field, or an equivalent combination of education and experience.
  • Two or more years of experience in a quantitative, analytics, investment, or performance measurementfocused role.
  • Experience with investment performance measurement, return calculations, or portfolio analytics.
  • Strong datadriven decisionmaking mindset with comfort working in ambiguous, unstructured problem spaces.
  • Processoriented approach with the ability to design scalable, repeatable analytical solutions.
  • Intellectual curiosity and willingness to challenge assumptions, methodologies, and existing analytical approaches.
  • High attention to detail and a strong instinct to reconcile, validate, and pressuretest data and results.
  • Experience with Snowflake, Python, dbt, and PowerBI preferred.
  • Strong proficiency in Python for data analysis, including pandas, numpy, and analytical workflows.
  • Experience building custom investment analyses, performance calculations, and repeatable analytical pipelines.
  • Proficiency in Power BI, including data modeling and integrating quantitative outputs into dashboards.
  • Advanced proficiency in Excel, including modeling and validation of analytical results.
  • Proficiency in Snowflake and dbt to query and build datasets.
  • Ability to interpret, scrub, process, and clearly explain complex quantitative results to nontechnical stakeholders

Skills You Will Have:

  • Adaptive Communication: Formulates strategies to be used to convey complex information about services, products, systems, or processes to targeted audiences; communicates and liaises between technical and non-technical audiences.
  • Attention to Detail: Focuses on specific details to spot and correct errors in advance of them being found and surpass quality expectations. Performs work with thorough proofreading for presentation, content, accuracy, and overall quality.
  • Financial Market Monitoring: Consistently tracks and analyzes financial market data and news, evaluates trends and events that may impact investment portfolios or financial decisions, and makes informed decisions based on this information. Stays up to date on economic indicators, market news, and global events, and understands how they relate to investment opportunities and risks.
  • Industry Knowledge: Demonstrates extensive knowledge of common practices, regulatory considerations, market trends and the competitive landscape within a particular industry / sector to better understand and address unique client requirements, challenges, and context.
  • Risk Evaluation: Assesses the significance of identified risks, makes judgments about the significance of the risk in relation to the organization's objectives and assesses whether the risk is acceptable or not. Considers factors such as the organization's risk appetite, risk tolerance, and risk management resources to help decision-makers determine which risks require further action and which can be accepted or tolerated.

Compensation Range:

Pay Range - Start:

$75,600.00

Pay Range - End:

$113,400.00

Geographic Specific Pay Structure:

Structure 110:

$83,200.00 USD - $124,800.00 USD

Structure 115:

$86,960.00 USD - $130,440.00 USD

We believe in fairness and transparency. It's why we share the salary range for most of our roles. However, final salaries are based on a number of factors, including the skills and experience of the candidate; the current market; location of the candidate; and other factors uncovered in the hiring process. The standard pay structure is listed but if you're living in California, New York City or other eligible location, geographic specific pay structures, compensation and benefits could be applicable, click here to learn more.


Grow your career with a best-in-class company that puts our clients' interests at the center of all we do. Get started now!


Northwestern Mutual is an equal opportunity employer that welcomes talented individuals of all backgrounds. We are committed to creating and maintaining an environment in which each employee can contribute creative ideas, seek challenges, assume leadership and continue to focus on meeting and exceeding business and personal objectives.



What Northwestern Mutual employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Northwestern Mutual logo

About Northwestern Mutual

Sourced by ZipRecruiter

Northwestern Mutual has been helping families and businesses achieve financial security for over 160 years through a distinctive planning approach that integrates risk management with wealth accumulation, preservation, and distribution. With more than $290 billion in assets, $30 billion in revenues and more than $1.9 trillion worth of life insurance protection in force, Northwestern Mutual delivers financial security to more than 4.6 million clients. People are the power behind Northwestern Mutual, and diversity makes us better. We are committed to reflecting and serving the marketplace. We do so by attracting and improving the engagement of those who bring their outstanding perspectives, ideas, and beliefs.

Industry

Finance and insurance

Company size

5,001 - 10,000 Employees

Headquarters location

Milwaukee, WI, US