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Retail Analytics Manager Jobs in Utah (NOW HIRING)

... retail analytic tools and advanced skills using Excel and PowerPoint strongly preferred * Digital marketing analytics experience * Experience using open source software tools in a CRM setting

Retail Media Manager

Pleasant Grove, UT · On-site

$51K - $64K/yr

As the Retail Media Manager, you will be responsible for managing an agency and hands-on execution ... Strong analytical and problem-solving skills. * Detail-oriented with strong organizational skills.

Retail Media Manager

Pleasant Grove, UT · On-site

$51K - $64K/yr

As the Retail Media Manager, you will be responsible for managing an agency and hands-on execution ... Strong analytical and problem-solving skills. * Detail-oriented with strong organizational skills.

With your retail knowledge and leadership abilities, you'll help oversee store operations, manage ... Well-developed planning, analytical, and problem-solving skills * Familiarity with wireless ...

With your retail knowledge and leadership abilities, you'll help oversee store operations, manage ... Well-developed planning, analytical and problem-solving skills Familiarity with wireless ...

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Retail Analytics Manager information

What does a Retail Analytics Manager do?

A Retail Analytics Manager is responsible for analyzing data related to retail sales, customer behavior, and market trends to help retailers make informed business decisions. They use data analytics tools to identify patterns, optimize inventory, improve customer experience, and increase profitability. Their work often involves collaborating with marketing, sales, and operations teams to develop strategies based on analytical insights. Ultimately, Retail Analytics Managers help retailers stay competitive by turning complex data into actionable recommendations.

How does a Retail Analytics Manager typically collaborate with merchandising and marketing teams to drive business outcomes?

A Retail Analytics Manager works closely with merchandising and marketing teams to analyze sales trends, customer behaviors, and promotional effectiveness. By providing actionable insights and data-driven recommendations, they help these teams refine product assortments, optimize pricing strategies, and develop targeted marketing campaigns. Regular cross-functional meetings and collaborative projects are common, ensuring that analytics inform key business decisions and support overall growth objectives. This collaborative approach enables the Retail Analytics Manager to directly influence store performance and customer satisfaction.

What is the difference between Retail Analytics Manager vs Retail Data Analyst?

AspectRetail Analytics ManagerRetail Data Analyst
Required CredentialsBachelor's degree in Business, Data Science, or related field; experience in analyticsBachelor's degree in Statistics, Data Analysis, or related field; entry to mid-level experience
Work EnvironmentOversees analytics teams, collaborates with management, strategic planningFocuses on data collection, analysis, reporting; supports decision-making
Employer & Industry UsageRetail chains, e-commerce companies, supermarketsRetail stores, online retailers, supply chain firms

The Retail Analytics Manager typically leads analytics initiatives, manages teams, and develops strategic insights, while the Retail Data Analyst focuses on analyzing data sets to support operational decisions. Both roles require strong analytical skills and familiarity with retail data tools, but the manager role involves more leadership and strategic planning responsibilities.

What are the key skills and qualifications needed to thrive as a Retail Analytics Manager, and why are they important?

A Retail Analytics Manager needs strong analytical skills, expertise in data analysis, and a background in business, statistics, or a related field, often supported by a bachelor’s or master’s degree. Proficiency in analytics tools such as SQL, Python, R, Tableau, and experience with retail data systems are typically required. Exceptional communication, problem-solving abilities, and stakeholder management help translate complex data insights into actionable business strategies. These skills ensure the effective use of data to drive sales, optimize operations, and support retail business growth.
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Senior Fraud Strategy and Analytics Manager

Raisin

Lehi, UT • Hybrid

Other

Medical, Dental, Vision, Retirement, PTO

Posted 20 days ago


Job description

Team

The Risk and Fraud Operations team plays a central role in safeguarding Raisin's business by monitoring, assessing, and mitigating risks across all operational areas. We are responsible for managing fraud prevention, detection and mitigation, investigations and recoveries, monitoring for financial crime events (AML, KYC) and implementing effective risk controls to support the company's growth. Our work bridges business, compliance, and technology-analyzing data, processes, and transactions to identify potential threats while also enabling smooth and secure customer experiences.
We collaborate closely with cross-functional teams (Product, Compliance, Customer Service, and Engineering) to design and execute risk and fraud management frameworks, enhance operational efficiency, and maintain a strong culture of accountability.
Your Responsibilities
As the Senior Fraud Strategy and Analytics Manager, you will be the driving force behind our fraud defense system. We are looking for a proven analytical mind from the financial services sector who can challenge our current thinking, build predictive fraud models, redesign existing fraud models, framework and processes. Using SQL, Python/R Ecosystems, Feature Engineering, you will dissect fraud trends, build predictive models from scratch, and implement sharp, real-time rules to prevent and detect fraud across our payment rails. 
This role reports to the Head of Risk and Fraud Operations and requires a highly capable and entrepreneurial individual who can balance deep technical hands-on execution with high-level strategy.

  • Advanced Fraud Strategy & Analytics
    - Uncover Trends: Conduct complex data analysis using SQL, Python and Feature Engineering to proactively identify emerging fraud patterns and system vulnerabilities before they impact the platform.
    - Deploy Fraud Rules: Design, test, and implement robust fraud prevention rules that successfully catch bad actors while maintaining a seamless experience for real customers.
    - Drive Strategy: Elevate Raisin US's capabilities by introducing industry best practices, new methodologies, and innovative fraud prevention strategies that we aren't using today.
    - KPIs & Dashboards: Build out data-driven dashboards to track fraud metrics, losses, and mitigation performance, presenting actionable findings directly to leadership.
  • Model Development & Maintenance
    - Build Predictive Models: Design, build, and deploy machine learning and predictive models utilizing Python to detect anomalies across the entire customer journey (onboarding, funding, and money movement).
    - Feature Engineering: Develop model features based on identity, device, behavioral, and transactional data.
    - Cross-Functional Delivery: Partner closely with Product and Engineering to integrate these models into our real-time production pipelines.
  • AML & Financial Crime Collaboration
    - Risk Profiling: Partner with the Compliance team to enhance customer risk profiling, transaction monitoring, and KYC/AML workflows.
    - Design low-friction, custom risk rules for identity verification, account takeover protection, and transaction monitoring.
    - Continuous Back-Testing: Routinely stress-test current rules against changing regulatory standards and evolving financial crime tactics.

Your Profile

  • Financial Services Background: 8+ years of experience in fraud risk management, analytics, or financial crime specifically within fintech, retail banking, or digital payments.
  • Master of Analytics: Exceptional analytical capabilities are your biggest asset. You love diving into raw data to solve complex puzzles.
  • Technical Stack: Highly proficient in SQL and Python for data manipulation, analytics, and building predictive models. Experience building out fraud dashboards is a must.
  • Payment System Domain Expertise: Deep understanding of Deposits and ACH is required; direct experience with modern instant payment systems like RTP and FedNow is highly preferred.
  • Rule & Model Builder: Proven track record of designing custom fraud rules and deploying machine learning or statistical models in a live environment.

Join our mission, join our team - and grow with us!

At Raisin, we care about each other and it is one of our top priorities to foster an open and caring environment in which everyone feels welcome and comfortable. Our culture is strongly driven by our ambitious team, which connects more than 75 different nationalities.

As part of our team, you will benefit from:

  • Flexible working hours and up to 28 days PTO accrued from your first month, plus 13 public holidays.
  • Employee Development Budget of $2,200 and 4 full training days per year.
  • Company 401k contribution of 5%.
  • Healthcare coverage contribution, including medical, dental and vision.
  • Commuter benefits and flexible working from home policy.
  • Regular team events and yearly Summer and Winter Party.