Senior Director, Analytics at Experian

Madison, Mississippi, United States -

Full Time

Start Date

Immediate

Expiry Date

25 Feb, 26

Salary

0.0

Posted On

27 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Asset Strategy, Analytics, Product Innovation, Statistical Modeling, Machine Learning, Python, SQL, Tableau, AWS, Data Monetization, Client Engagement, Leadership, Regulatory Compliance, Data Visualization, M&A Support, Business Case Development

Industry

Information Services

Description

Company Description Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create digital marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realise their financial goals and help them to save time and money. We operate across a range of markets, from financial services to healthcare, automotive, agrifinance, insurance, and many more industry segments. We invest in people and new advanced technologies to unlock the power of data and to innovate. A FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 23,300 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com. Job Description We are looking for a visionary yet hands-on Senior Director to lead the evaluation of new data assets (raw, enriched, or consumer-aggregated) and to lead our consumer-permissioned data strategy from an analytics perspective. We are looking for both senior team member influence and technical fluency, with the ability to engage executives on strategic direction while guiding teams through the practical execution of analytics and product development. You will report to the VP of Analytics Product Build, Innovation and Scores. You will work remote from the United States. You thrive in cross-functional environments, can navigate complex data-driven business cases, and moves from coding in Python to valuing acquisition targets to leading client discussions. You'll have opportunity to: Data Asset Strategy & Evaluation Lead the assessment of new data sources, including coverage, quality, compliance, and commercial potential. Define and lead the consumer-permissioned data strategy from an analytics perspective, ensuring regulatory compliance and business understanding. Develop valuation frameworks to guide investment in and acquisition of data assets. Analytics & Product Innovation Build and deploy statistical, predictive, and machine learning models to extract relevant insights from data. Partner with Product teams to translate evaluated data opportunities into high-value features and scalable products. Design compelling visualizations and dashboards in Tableau to communicate findings to executives, clients, and strategic partners. M&A Support & Business Case Development Work with the M&A team to assess the data value of acquisition targets and support due diligence processes. Present clear, data-backed business cases to inform executive decision-making. Identify opportunities for synergistic integration of acquired datasets with existing assets. Leadership & Client Engagement Lead client-facing meetings to present analytical findings, demonstrate product capabilities, and guide solution adoption. Develop analytics teams, promoting a culture of innovation, and measurable impact. Be an expert on new data trends, regulatory developments, and monetization strategies. Qualifications Master's degree in a technical field such as Data Science, Computer Science, Statistics, Engineering, or a related discipline. 10+ years of industry experience in analytics, data strategy, or related fields; minimum 5 years in a leadership role. Proven experience evaluating, monetizing, and integrating data assets. Technical expertise in Python, SQL, Tableau, and experience with AWS. Background in statistical modeling, machine learning, and data monetization strategies. Additional Information Benefits/Perks Great compensation package and bonus plan Core benefits including medical, dental, vision, and matching 401K Flexible work environment, ability to work remote, hybrid or in-office Flexible time off including volunteer time off, vacation, sick and 12-paid holidays Explore all our exciting benefits here: https://yourexperianbenefits.com/cand-index.html At Experian, our people and culture set us apart. We're deeply committed to creating an environment where everyone feels they belong and can excel. From inclusion and authenticity to work/life balance, development, wellness, collaboration, and recognition, we focus on what truly matters. Our people-first approach has earned us global recognition: World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ 2025 in 26 countries, and Glassdoor Best Places to Work 2024, among others. Want to see what life at Experian is really like? Explore Experian Life on social or visit our careers site. Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay range for this position is listed above. Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education. You will be also eligible for a variable pay opportunity. Experian is proud to be an Equal Opportunity Employer for all groups protected under applicable federal, state and local law, including protected veterans and individuals with disabilities. Innovation is an important part of Experian's DNA and practices, and our inclusive workforce allows everyone to succeed and bring their whole self to work. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity. #LI-Remote

Responsibilities

Lead the evaluation of new data assets and consumer-permissioned data strategy from an analytics perspective. Build and deploy statistical models and partner with product teams to translate data opportunities into scalable products.