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About This Role
About Fusion92
Fusion92 is a Marketing Transformation Partner built for what’s next. We help brands solve complex business problems through a connected ecosystem of data, technology, media, and creativity, designed to drive measurable growth at scale.
Powered by proprietary tools, AI-enabled intelligence, and fearless thinking, we don’t just execute marketing, we transform how marketing works.
Fusion92 operates through hybrid hubs in Chicago and Detroit, with remote teams in Austin, Denver, and across the U.S.
Built by Bold People
Our difference isn’t just what we do—it’s how we do it and who we do it with. Fusion92 is built by people who are relentlessly curious, unafraid to challenge convention, and committed to doing work that matters.
We bring together strategists, data scientists, technologists, media experts, creatives, consultants, operators, and innovators who thrive at the intersection of insight and execution. From launching new products to developing patented innovations and award-winning ideas, we help clients move forward with confidence and precision.
A Culture Designed for Growth
At Fusion92, we believe great work happens when friction is removed and people are trusted to lead. Our culture is grounded in values that show up in our work, our decisions and our teams:
- Curious – We challenge assumptions and ask better questions
- Fearless – We take smart risks and lead through change
- Team-Focused – We win together across disciplines and time zones
- Leaders at Every Level – Ownership and initiative matter more than titles
Why Join Us
Fusion92 is for people who want to build, not just belong. You’ll work on meaningful challenges, collaborate with smart, driven teammates, and have the autonomy to shape how work gets done.
If you’re excited by complexity, motivated by impact, and looking for an environment where curiosity is fueled and leadership is expected, there’s a place for you here.
Our people power our transformation.
That’s where you come in.
DATA SCIENTIST
Overview
The Data Scientist designs and delivers advanced analytical solutions that power strategic decision-making across the organization. This role transforms complex data into actionable insights, predictive models, and scalable machine learning solutions that drive marketing performance, deepen customer understanding, and improve business outcomes.
Working cross-functionally with strategy, media, client services, and engineering teams, the Data Scientist translates business challenges into data science initiatives and communicates results clearly to both technical and non-technical stakeholders. This role plays a critical part in elevating analytical rigor, innovation, and impact across the organization.
What You’ll Do
- Design, develop, and deploy predictive models, segmentation frameworks, and machine learning solutions to support marketing performance, targeting, and customer analytics.
- Analyze large, complex datasets to uncover insights that inform strategic and tactical business decisions.
- Build and maintain robust data pipelines to ensure clean, reliable, and well-structured data for analysis and modeling.
- Ensure model integrity and performance through validation, QA processes, documentation, and ongoing monitoring.
- Design and execute experiments (including A/B and multivariate tests) to evaluate campaign effectiveness and optimize outcomes.
- Partner with strategy, media, and client services teams to translate business needs into scalable, data-driven solutions.
- Present findings and recommendations through clear storytelling, visualizations, and executive-ready materials.
- Contribute to team development through collaboration, peer review, knowledge sharing, and cross-training.
- Stay current with emerging data science tools, techniques, and best practices, helping evolve the team’s capabilities and standards.
Requirements:
KNOWLEDGE/SKILLS/ATTRIBUTES REQUIRED:
- 1-3 years of applied data science experience, ideally in marketing, media, or customer analytics environments.
- Advanced proficiency in SQL for complex querying and data manipulation.
- Strong Python skills for data analysis, modeling, automation, API integration, and production workflows.
- Hands-on experience with machine learning frameworks (e.g., scikit-learn, XGBoost) and cloud/data platforms (e.g., AWS, Azure, Snowflake).
- Strong foundation in statistics, experimental design, and computer science principles.
- Experience building and deploying models in production environments.
- Familiarity with marketing use cases such as audience segmentation, attribution modeling, audience creation, and trade area analysis.
- Experience with Alteryx is a strong plus.
- Experience with visualization tools such as Tableau (or similar BI tools) is a plus.
- Strong problem-solving skills, attention to detail, and the ability to work independently and collaboratively.
- Excellent communication skills with the ability to simplify complex analyses for diverse audiences.
- Understanding of data privacy regulations and ethical considerations in modeling.
Location:
This role may be based out of our Chicago, Detroit, Denver or Austin hubs. We will consider candidates outside these markets but prefer alignment to our core hubs.
Equal Opportunity Employer
Fusion92 is proud to be an Equal Opportunity Employer. We are committed to building a diverse and inclusive workplace and do not discriminate on the basis of race, color, religion, sex (including pregnancy), gender identity or expression, sexual orientation, national origin, age, disability, veteran status, genetic information, or any other status protected by applicable federal, state, or local laws.
We encourage individuals from all backgrounds to apply and are committed to providing reasonable accommodations throughout the hiring process.
In compliance with applicable pay transparency laws, the salary range for this role is $65,000 – $90,000, which represents the minimum and maximum base salary we reasonably expect to pay for this position at the time of posting. Actual compensation will be determined based on factors such as experience, skills, qualifications, internal equity, and geographic location. This role may also be eligible for additional compensation, including bonuses and benefits.
Fusion92 is committed to providing reasonable accommodations throughout the hiring process. If you require an accommodation, please let us know.
Salary Context
This $65K-$90K range is in the lower quartile for Data Scientist roles in our dataset (median: $161K across 138 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 9,079 AI roles we're tracking, Data Scientist positions make up 4% of the market. At Fusion92, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $190,000 based on 1,503 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($77K) sits 59% below the category median. Disclosed range: $65K to $90K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Fusion92 AI Hiring
Fusion92 has 1 open AI role right now. They're hiring across Data Scientist. Based in Chicago, IL, US. Compensation range: $90K - $90K.
Location Context
AI roles in Chicago pay a median of $193,440 across 429 tracked positions. That's 9% below the national median.
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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