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About This Role
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Team Overview
The Financial Services Analytics team partners with banks, lenders, insurers, and other financial institutions to solve complex business challenges using advanced analytics and TransUnion data assets. The team delivers predictive modeling, risk analytics, fraud solutions, and business intelligence insights that help clients make smarter business decisions and drive measurable outcomes. This role reports to Director of Data Science and Analytics.

This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week. Role Overview and Core Responsibilities
- Develop predictive models and advanced analytics solutions for clients across credit risk, fraud, insurance, and marketing use cases.
- Lead analytics engagements from project design and development through implementation, validation, and client presentation.
- Partner with internal stakeholders, sales teams, and external clients to identify opportunities where data science can create business value.
- Conduct descriptive, predictive, and prescriptive analyses to solve complex customer business challenges.
- Translate analytical findings into actionable business recommendations and present results to technical and non-technical audiences.
- Design, build, and optimize data extraction, segmentation, and statistical analysis processes using large-scale datasets.
- Create repeatable analytical frameworks and process improvements that increase efficiency and scalability.
- Support business development efforts through project proposals, client presentations, and analytic consulting.
Required Knowledge and Experiences
- Master’s degree or PhD in Statistics, Applied Mathematics, Financial Mathematics, Computer Science, Engineering, Operations Research, or another highly quantitative field.
- 1+ years of experience performing analytics, data science, statistical modeling, or quantitative analysis.
- Understanding of U.S. financial services risk management practices and how data-driven insights support business decisions.
- Experience within financial services, insurance, fraud, credit risk, digital marketing, or related industries.
Required Technical Skills
- Python or R for statistical analysis, predictive modeling, and data science solution development.
- SQL for data extraction, transformation, segmentation, and analysis.
- Experience working with large datasets and distributed data platforms such as Hive and Spark.
- Knowledge of machine learning, predictive analytics, statistical modeling, and business intelligence techniques.
We’re also looking for the preferred skills below. Whether you are proficient or could use some brushing up, we’re happy to support your career development and growth in:
- Experience working with credit bureau data, credit risk models, or financial services analytics.
- Exposure to programming languages such as Java or C/C++.
- Experience in client-facing consulting or analytics advisory engagements.
- Knowledge of fraud analytics, insurance analytics, or marketing analytics solutions.
Benefits that support every part of your life:
At TransUnion, we design benefits to help you feel well, do well, and plan well—from day one.
For Your Health : Enjoy day-one eligibility for medical, dental, and vision coverage, plus supplemental plan options. Spousal, domestic partner, and other eligible dependent coverage is available on select plans. Choose tax‑advantaged HSA and FSA accounts to make everyday care more affordable.
For Your Protection : We’ve got your back with company‑paid basic life and AD&D, optional voluntary life and AD&D for you and your family, and short‑ and long‑term disability. You can also opt into a legal plan, pet insurance, and travel accident coverage.
For Your Family : From adoption assistance and fertility planning coverage to caregiver support, we’re here for every chapter. Access Dependent Care FSA for possibility of an employer match, a complimentary Care@Work membership, and up to 12 weeks of paid parental leave with eligibility for a thoughtful, gradual return.
For Your Future : Build toward what’s next with our 401(k) with employer match and Employee Stock Purchase Plan (ESPP). Tap financial wellness resources, career coaching, and optional long‑term care insurance to plan confidently.
For You : Grow and recharge with tuition reimbursement, flexible time off for exempt employees or paid time off for nonexempt employees, up to 12 paid holidays per year, commuter benefits, employee discounts, charitable gift matching, and paid volunteer time off, plus corporate volunteer events that make it easy to give back.
For Your Wellness : Access 24/7 support including professional therapy, coaching, and emotional well‑being programs alongside guided meditation and resources that support physical, mental, social, and financial wellness.
We are committed to being a place where diversity is not only present, it is embraced. As an equal opportunity employer, all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability status, veteran status, genetic information, marital status, citizenship status, sexual orientation, gender identity or any other characteristic protected by law. Additionally, in accordance with Section 503 of the Rehabilitation Act of 1973 and the Vietnam Era Veterans’ Readjustment Assistance Act of 1974, TransUnion takes affirmative action to employ and advance in employment qualified individuals with a disability and protected veterans in all levels of employment and develops annual affirmative action plans. Components of TransUnion’s Affirmative Action Program for individuals with disabilities and protected veterans are available for review to any associate or applicant for employment upon request by contacting [email protected] .
Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, Fair Chance Initiative for Hiring Ordinance, and the California Fair Chance Act.
Adherence to Company policies, sound judgment and trustworthiness, working safely, communicating respectfully, and safeguarding business operations, confidential and proprietary information, and the Company’s reputation are also essential expectations of this position.
Pay Scale Information:
The U.S. base salary range for this position is $67,500.00 - $112,500 annually. *The salary range for this position reflects a reasonable estimate of the range of compensation for this job. At TransUnion, actual compensation is based on careful consideration of additional factors such as (but not limited to) an individual’s education, training, work experience, job-related skill set, location, and industry knowledge, as well as the scope and responsibilities of the position and market considerations. Regular, fulltime non-sales positions may be eligible to participate in TransUnion’s annual bonus plan. Certain positions may be also eligible for long-term incentives and other payments based on applicable company guidance and plan documents.
 TransUnion Overview:
At TransUnion, we encourage and are committed to creating a real, positive impact and shared sense of purpose within our Workforce for Good , which empowers our people to grow, innovate and contribute to a better future for our communities and customers. We strive to build an environment where our associates are in the driver’s seat of their professional development— while having access to help along the way. We recognize that success comes when our associates thrive both professionally and personally; that’s why we prioritize work/life flexibility and offer resources for our teams across the globe to collaborate and drive excellence.
Be a part of our Workforce for Good – you’ll work with great people, pioneering products and cutting-edge technology.
TransUnion's Internal Job Title:
Sr Analyst, Data Science and Analytics Company:
TransUnion LLC
Salary Context
This $67K-$112K 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 TransUnion, 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 ($90K) sits 53% below the category median. Disclosed range: $67K to $112K.
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.
TransUnion AI Hiring
TransUnion has 3 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist. Positions span Chicago, IL, US, Bengaluru, Karnataka, India. Compensation range: $112K - $225K.
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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