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Student Shadow Data Analytics Jobs in Wisconsin (NOW HIRING)

WI ยท On-site

$180 - $260/hr

At our core, Darkroom is a human services company powered by Shadow, a universal AI commerce layer ... data schemas, and analytical models Shadow's agents reason with, and working directly with ...

New

Sr. Data Analyst

Waukesha, WI ยท On-site +1

$86K - $108K/yr

The Senior Data Analyst is a strategic and technical role within Information Technology responsible ... Experience supporting institutional effectiveness, enrollment analytics, student success, or ...

Sr. Data Analyst

Waukesha, WI ยท On-site

$86K - $108K/yr

... analytics, student success, or operational reporting initiatives. Technical Skills: โ€ข Experience ... data warehousing, ETL/integration processes, or cloud analytics platforms. โ€ข Knowledge of data ...

Student Analyst II

Sheboygan, WI ยท On-site

$74K - $91K/yr

This isn't a "shadow and observe" role. You'll work with clients alongside BCBAs who are invested ... Collect accurate, timely behavioral data and analyze it to support data-driven recommendations

Posted today

Data Engineer

Milwaukee, WI ยท On-site

$112K - $135K/yr

We prioritize student success, access to education, and service in our work to educate well-rounded ... Minimum of 3 years' experience in data analytics or data solutions Demonstrated experience writing ...

Data Analysis Tutor

Milwaukee, WI ยท Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Data Analysis tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Data Analysis Tutor

Madison, WI ยท Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Data Analysis tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

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Student Shadow Data Analytics information

What is a student shadow data analytics?

Student Shadow Data Analytics refers to the process of collecting and analyzing data about students as they are observed or 'shadowed' through their daily academic activities. This analysis helps educators and administrators understand student behaviors, learning patterns, and engagement levels. Insights from this data can be used to improve teaching strategies, personalize learning experiences, and identify areas where students may need additional support. Student shadowing combined with data analytics provides a comprehensive view of the student experience in educational settings.

What types of projects or tasks can I expect to work on as a student shadow in data analytics?

As a Student Shadow in Data Analytics, you will typically observe and assist with projects such as data collection, cleaning, and visualization. You might help analyze datasets to uncover trends or support team members in preparing reports and presentations for stakeholders. This role often involves collaborating closely with experienced data analysts and learning how to use industry-standard tools like Excel, SQL, or Python. It's a great opportunity to see how real-world business problems are solved using data-driven approaches.

What is the difference between Student Shadow Data Analytics vs Data Analyst?

AspectStudent Shadow Data AnalyticsData Analyst
Required CredentialsTypically enrolled in a related degree program, no formal certification requiredBachelor's degree in data science, statistics, or related field; certifications like SQL or Tableau often preferred
Work EnvironmentObservational role, often unpaid or internship-based, in educational or entry-level settingsFull-time professional role in corporate, finance, healthcare, or tech industries
Employer & Industry UsageEducational institutions, internships, entry-level projectsBusinesses, consulting firms, government agencies
Common Search & ComparisonYesYes

The main difference between Student Shadow Data Analytics and Data Analyst lies in experience, credentials, and work environment. Student Shadow roles are typically observational or internship-based, focusing on learning, while Data Analysts are full-time professionals performing data analysis tasks in various industries.

What are the key skills and qualifications needed to thrive as a student shadow in data analytics, and why are they important?

To thrive as a Student Shadow in Data Analytics, you should have a foundational understanding of statistics, data interpretation, and basic programming, often gained through coursework or related academic projects. Familiarity with tools such as Microsoft Excel, SQL, and introductory data visualization software (like Tableau or Power BI) is typically expected. Eagerness to learn, attention to detail, and strong communication skills help you stand out in this observational and learning-focused role. These skills are crucial because they enable you to quickly absorb complex concepts, contribute to discussions, and make the most of your shadowing experience in a real-world data analytics environment.
What are popular job titles related to Student Shadow Data Analytics jobs in Wisconsin? For Student Shadow Data Analytics jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Student Shadow Data Analytics jobs in Wisconsin look for? The top searched job categories for Student Shadow Data Analytics jobs in Wisconsin are:
What cities in Wisconsin are hiring for Student Shadow Data Analytics jobs? Cities in Wisconsin with the most Student Shadow Data Analytics job openings:
Infographic showing various Student Shadow Data Analytics job openings in Wisconsin as of August 2026, with employment types broken down into 27% Internship, and 73% Full Time. Highlights an 74% In-person, and 26% Remote job distribution.

Associate Director, Data Strategy & Analytics

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WI โ€ข On-site

$180 - $260/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 2 days ago

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Job description

About Darkroom

Darkroom is the leading next-generation growth marketing firm engineering the brands of tomorrow. Founded in 2017, we set out to redefine what a modern agency could be, by replacing the inertia of legacy advertising behemoths with a model built for speed, intelligence, and measurable impact.

At our core, Darkroom is a human services company powered by Shadow, a universal AI commerce layer that integrates executive-level strategy with proprietary agentic technology. This fusion enables our teams to deliver outsized returns by enhancing creative output, operational efficiency, and revenue generation across every stage of the customer journey.

Our track record speaks for itself: billions in attributable revenue driven across e-commerce marketplaces, media networks, DTC ecosystems, and social commerce platforms. Every engagement feeds into our proprietary data infrastructure, enabling a continuous feedback loop that accelerates growth, improves margins, and compounds results across our client portfolio.

What began as a boutique design studio has evolved into one of the fastest-growing private companies in America and among the most effective performance media agencies of the 2020s. Our founders were recognized by Forbes 30 Under 30 for advancing the intersection of technology, marketing, and advertising, cementing Darkroom's role as a defining player in the future of media innovation.

About the Role

Part senior growth marketer, part data scientist, part appliedโ€‘AI builder โ€” you turn the way elite marketers think into the data models, metrics, and schemas that power Shadow's intelligence layer. The majority of your time (roughly 75%) is spent on the product: designing the metric logic, data schemas, and analytical models Shadow's agents reason with, and working directly with marketing teams to translate what they actually do into structure the product can act on.

The remaining time (roughly 25%) is spent on measurement of live media programs โ€” guiding incrementality testing, power analysis, and MMM work, and partnering with Paid Media and Growth Strategy to turn test results into budget decisions.

This is for someone who's spent years in the work and now wants to lean into the technology โ€” leveraging hard-won marketing experience to build, not to manage accounts. The product side of this role is not client-facing; the measurement side is internal-facing too, working through Darkroom's own media teams rather than owning client relationships directly.

What We're Building

We're empowering small teams with technology that makes it easier to market and grow businesses. Our current focus is to help consumer brands shift from "workflow automation" to "agent management" within their marketing operations. Shadow is the AI coordination layer โ€” providing shared AI memory, centralized agent control, and model orchestration for marketing teams.

The Agency Behind the Product

Shadow is built alongside Darkroom โ€” a performance marketing agency that's been operating for 10 years, employs 100+ people, runs 100+ clients at a time, and has worked with over 1,000 consumer brands. That's our edge: Shadow isn't a generic AI wrapper; it's a decade of real campaign tradecraft being codified into a system. Darkroom is both our proving ground and our first user. This role plugs directly into that knowledge and turns it into product.

What You'll Own

Product

  • Design the analytical models and metric logic the agent reasons with โ€” contribution margin (CM3), acquisition truth (aMER, NCAC), cohort LTV/payback, ad spend efficiency and marginalโ€‘return analysis, incrementality testing (geo lifts, conversionโ€‘lift, MMM calibration) โ€” from raw platform data to decisionโ€‘ready insight.

  • Define the schemas that encode marketing tradecraft: how creative, channel, financial, and customer data connect into a queryable picture of a brand.

  • Own accuracy and judgment โ€” what's loadโ€‘bearing vs. noise, where attribution lies, how to compute metrics that survive operator scrutiny.

  • Spec the model; partner with data eng to build the pipeline and the AI team to wire it into agent skills.

Measurement of media programs

  • Guide incrementality testing strategy across Darkroom's paid media programs โ€” geo holdouts, matchedโ€‘market tests, and conversionโ€‘lift studies โ€” and run the power analysis to size tests correctly before spend is committed.

  • Support MMM strategy, vendor evaluation, and model calibration where programs need it.

  • Partner with Paid Media and Growth Strategy teams to design tests up front and translate results into clear, executiveโ€‘ready budget recommendations.

Must Haves
  • Ran growth at one or more highโ€‘growth DTC / omniโ€‘channel consumer brands โ€” you've managed paid media tactically, not just supervised people who did.

  • Fluency across the full marketing mix (Meta + Google, plus TikTok, email/SMS, marketplace, organic) โ€” you think in MER/CM/LTV/iROAS, not platform ROAS.

  • Real data science chops: SQL + Python/notebooks, statistical reasoning, building and validating metric models against messy realโ€‘world data.

  • Ability to translate between marketer intuition and rigorous structure โ€” and a strong opinion about which metrics actually matter.

  • Handsโ€‘on experience designing and interpreting incrementality tests โ€” geo holdouts, matchedโ€‘market testing, conversion lift โ€” including power analysis/preโ€‘test sizing.

  • Experience with MMM, either handsโ€‘on or through vendor/partner management.

  • Strong written and verbal communication โ€” you can explain measurement tradeoffs and model logic clearly to nonโ€‘technical executives and marketers.

Nice to Have
  • Familiarity with modern warehouse/analytics stacks (BigQuery, dbt) โ€” enough to design schemas and collaborate with eng.

  • Agency or multiโ€‘brand background (pattern recognition across accounts).

  • Built attribution models, forecasting/MMM, or internal analytics dashboards.

  • Experience with CDPs, serverโ€‘side tracking, clean rooms, exposure logs, or other privacyโ€‘safe measurement environments.

Culture Fit
  • A power AI user. You've embedded AI into every workflow you touch and you think in systems โ€” not oneโ€‘off prompts, but repeatable structures that compound.

  • Entrepreneurial. You don't need much direction to move fast, you pivot when the situation demands it, and what you ship is productionโ€‘grade, not a prototype you hand off for someone else to finish.

Not the bar: deep dataโ€‘engineering/infra ownership, or leading dayโ€‘toโ€‘day client relationships. We're hiring for science, judgment, and product craft โ€” not pipeline plumbing or account management.

What It's Like to Work at Darkroom

Darkroom is not a typical agency. We are looking for A players who want to build something great. We move fast, think deeply, and expect every team member to bring insight and rigor to everything they touch. We hold a high bar for performance, creativity, and ownership โ€” but we also support each other relentlessly. No egos, no red tape โ€” just worldโ€‘class talent building something remarkable.

We believe in autonomy with accountability, truth over comfort, and outcomes over optics.

  • Unlimited PTO + US holidays: Rebooting is part of the work. Take the time you need to stay sharp.

  • Remoteโ€‘First Culture: Many roles are fully remote. Employees based in or near our New York or Lisbon HQs are expected to work hybrid with weekly inโ€‘office time. Hub locations include Brazil and Spain.

  • Health & Wellness: Companyโ€‘sponsored medical, dental, and vision coverage.

  • Finances, growth, and retirement: Darkroom offers a robust 401(k) program with company match and profitโ€‘sharing opportunities to help you save and grow as the company grows.

  • Parental Leave: Flexible parental leave to support new parents during this important transition.

  • Growth: Our interdisciplinary model gives every Darkroomer exposure far beyond their core role. Grow your skills, expand your influence, and stay at the forefront of the industry.

Equal Opportunity Statement

Darkroom is an equal opportunity workplace โ€” we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national orientation, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

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