$100k - $140k
Salary: $100,000 - 140,000 per year Requirements: We require six or more years of professional experience in data engineering, data operations, data platform operations, or a related discipline. We prefer a bachelors deg…
Engineering & IT · Milwaukee, WI
Data Scientist jobs in Milwaukee, WI
Data scientists turn raw data into decisions and products, using statistics, experimentation, and machine learning to answer questions the business could not otherwise settle.
360
Open roles today
$37–$91/hr
Typical pay range
$124k
Median, full-time
8
Fresh in this list
No email, no resume, no sign-up. Save any listing below and you start anonymously.
You're signed in. Saving a listing drops it straight into your pipeline.
01
Open data scientist roles
12 shown of 360 · sorted by freshness
success -- so we give you unlimited access to everything you need to create innovative new solutions on our engineering team. As a Sr. Data Engineer, you will design, build, and support scalable data solutions that enabl…
$149k - $189k
thermal sciences discipline; a PhD is preferred. We look for 5+ years of relevant experience in thermal systems, HVAC/R, hydronics, data center cooling, heat transfer, or applied thermal-fluid product development; advanc…
We are looking for a Data Engineer to help shape and expand a cloud-focused data environment that supports analytics, operational reporting, automation, and emerging AI use cases. Based in Brookfield, Wisconsin, this pos…
$132.26k - $155.6k
career. Try new things, learn new skills and discover what you excel at—all from Day One.Job DescriptionJob Duties -Responsible for big data/ analytics projects that gather and integrate large volumes of data. -Specializ…
and resources of the fastest-growing brand in the construction industry to make it happen.Your Role on Our Team:The Senior Manager of Data Engineering leads teams that design, build, operate, and continuously improve ent…
leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global de…
Senior Snowflake Data Engineer / Architect with Cortex AI Job Summary We are seeking a Senior Snowflake Data Architect with strong hands-on experience in Snowflake, data architecture, dimensional modeling, SQL, and enter…
WEC Business Services LLC Job Responsibilities * Establishes and implements appropriate standards and criteria for data security requirements * Design, develop, deploy and manage enterprise data security solutions includ…
Data Security Engineer About the Opportunity AEBS is seeking a talented cybersecurity professional to help protect sensitive data across enterprise systems and platforms. The Data Security Engineer role offers the opport…
infrastructure using Docker, Kubernetes, and cloud services. Monitor model performance, data quality, system health, and production workloads. Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps te…
$117.5k - $249.78k
0 - 249,780 per year Requirements: We look for 10+ years of professional experience applying AI/ML to deliver strong commercial data science outcomes. We need expertise with electronic health records or unstructured data…
02
What data scientists earn in Milwaukee
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $37–$50 | $76k–$104k |
| Mid level | $50–$68 | $104k–$142k |
| Senior | $66–$91 | $138k–$190k |
Adjusted for the Milwaukee market from national ranges.
03
What employers ask for
The skills these listings keep naming
Python (pandas, scikit-learn)SQLStatistics and A/B testingMachine learning fundamentalsData visualizationExperiment designCommunicating with stakeholdersDomain and product sense
04
Interview questions worth rehearsing
With the thing the interviewer is actually listening for
Walk me through a data project that changed a decision.
Structure it as question, approach, finding, action. Projects that ended in a decision — even 'we did not launch' — beat technically impressive analyses that went nowhere.
How would you design an A/B test for a new feature?
Cover the metric, randomization unit, sample size, and duration, plus a pitfall like peeking or interference. Practical rigor is what is being tested.
Your model performs well offline but poorly in production. Why might that be?
Discuss train/serve skew, data leakage, distribution shift, and feedback loops. Listing several plausible causes and how you would check each is the strong answer.
Explain p-values or confidence intervals to a non-technical stakeholder.
Use plain language and a concrete scenario, and resist overstating certainty. They are testing whether your statistics survive translation.
How do you handle missing or messy data?
First ask why it is missing — the mechanism matters more than the imputation method. Then discuss options and how the choice affects conclusions.
When would you not use machine learning for a problem?
When a rule, a query, or a simple heuristic wins on cost and interpretability. Knowing when ML is overkill signals maturity.
How do you decide which metric a team should optimize?
Talk about proxy versus true goals, gameability, and counter-metrics. A story about a metric that backfired is very effective here.
05
Resume tips that move the needle
For data scientists specifically — generic advice costs you here
01
Lead every bullet with the business result — revenue, retention, cost — and put the method second.
02
Specify your stack concretely: Python libraries, SQL dialects, experimentation platforms, and any production ML experience.
03
Distinguish shipped work from research; 'model serving 2M users' and 'notebook analysis' are different claims.
04
Keep one or two public projects or publications linkable, tailored to the industry you are targeting.
05
Name the size and kind of data you worked with — event streams, tabular, text — so teams can map you to their problems.
06
Where this role goes
Typical progression
01
Junior Data Scientist
02
Data Scientist
03
Senior Data Scientist
04
Staff Data Scientist
05
Head of Data Science
Ten quiet minutes a day
Applying for data scientist jobs in Milwaukee?
Robbi carries this page into your first day: your role, your city, your shift preference. Then it hands you a few small things each morning and keeps the pipeline honest.
Save what looks right here, then let Robbi hand you a few small things each morning and keep the follow-ups honest.
Start with this search
No email, no resume, no sign-up.
Open your tracker
Everything you saved is already there.