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Director Predictive Analytics Jobs in Utah (NOW HIRING)

Apply AI/ML methods to enhance predictive analytics, anomaly detection, and risk identification ... Partner with program directors, data scientists, and software engineers to operationalize models ...

Evaluate and prioritize Generative AI, predictive analytics, machine learning, and intelligent ... Perform direct troubleshooting and root cause analysis when necessary. * Guide teams through issue ...

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Perform other duties as needed and directed by leadership What You'll Need to Get the Job Done ... process automation (RPA), or predictive analytics * Background in training development or ...

Perform other duties as needed and directed by leadership What You'll Need to Get the Job Done ... process automation (RPA), or predictive analytics * Background in training development or ...

Apply AI/ML methods to enhance predictive analytics, anomaly detection, and risk identification ... Partner with program directors, data scientists, and software engineers to operationalize models ...

... AI, and predictive analytics. HSB is redefining insurance by focusing on prevention-not just ... Monitor, evaluate, and recommend enhancements to underwriting processes for direct cyber products ...

Work hand-in-hand with Data Science and Finance to refine predictive LTV (pLTV) models, analyze ... leadership (Director+) role managing a highly technical team and massive media budgets ($10M+

Director, Insights & Data What You Will Own * End-to-End Product Analytics Success Insights: You ... predictive models that empower product leaders to leverage deep insights to drive business ...

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Director Predictive Analytics information

What are the key skills and qualifications needed to thrive as a Director of Predictive Analytics, and why are they important?

To thrive as a Director of Predictive Analytics, you need advanced expertise in statistics, machine learning, and data analysis, typically supported by a degree in mathematics, statistics, computer science, or a related field. Familiarity with tools such as Python, R, SQL, cloud-based analytics platforms, and relevant certifications in data science or analytics software are highly valued. Exceptional leadership, strategic thinking, and communication skills help you translate complex data insights into actionable business strategies and manage cross-functional teams effectively. These competencies are crucial for driving data-informed decision-making and maximizing the value of predictive analytics within an organization.

What does a director of analytics do?

A director of analytics oversees data analysis teams to develop strategies that improve business performance through data-driven insights. They manage analytics projects, interpret complex data, and communicate findings to stakeholders, often using tools like SQL, Python, or Tableau. This role requires strong leadership, statistical knowledge, and experience in predictive modeling and data management.

What is the highest paying job in data analytics?

The highest paying roles in data analytics are often executive-level positions such as Chief Data Officer or Director of Predictive Analytics, which can offer salaries exceeding $150,000 annually. These roles typically require advanced skills in data modeling, leadership, and experience with tools like Python, R, or SQL, along with strategic decision-making responsibilities.

What is the difference between Director Predictive Analytics vs Data Scientist?

AspectDirector Predictive AnalyticsData Scientist
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; often requires leadership experienceBachelor's or Master's in Data Science, Statistics, Computer Science, or related field
Work EnvironmentLeads teams, manages projects, collaborates with executivesAnalyzes data, develops models, reports findings
Employer & Industry UsageUsed in corporate, finance, healthcare, and tech sectors for strategic decision-makingCommon across tech, finance, marketing, and research sectors for data analysis

The main difference is that the Director Predictive Analytics oversees teams and strategic projects, focusing on leadership and high-level decision-making, while Data Scientists primarily analyze data and build models to derive insights. Both roles require strong analytical skills and knowledge of data tools, but the director position emphasizes management and strategic alignment.

What skills are needed for predictive analytics?

Predictive analytics professionals need strong skills in statistical analysis, data modeling, and machine learning algorithms. Proficiency in programming languages such as Python or R, experience with data visualization tools, and knowledge of database management are also essential for success in this role.

Will AI replace big data?

As a Director of Predictive Analytics, you understand that AI enhances big data analysis by automating data processing and improving predictive models. AI tools like machine learning algorithms are used to extract insights from large datasets, but they complement rather than replace the need for big data infrastructure and skilled analysts. Both are essential for effective data-driven decision-making in organizations.

What are the typical collaboration points for a Director of Predictive Analytics within an organization?

A Director of Predictive Analytics regularly collaborates with cross-functional teams, including data engineers, data scientists, business stakeholders, and IT departments. They are responsible for translating business needs into analytical solutions, ensuring data quality, and integrating predictive models into operational systems. Strong communication is essential, as the director must bridge technical teams and business leaders to drive data-driven decision-making throughout the organization.

What does a Director of Predictive Analytics do?

A Director of Predictive Analytics leads teams that use data, statistical algorithms, and machine learning techniques to forecast future outcomes and trends for a business. They are responsible for developing and implementing predictive models that drive strategic decisions in areas such as marketing, operations, and risk management. This role often involves collaborating with executives, data scientists, and IT professionals to ensure analytics solutions align with organizational goals. Additionally, the Director oversees data quality, project management, and the adoption of analytical best practices across the company.
What are the most commonly searched types of Predictive Analytics jobs in Utah? The most popular types of Predictive Analytics jobs in Utah are:
What cities in Utah are hiring for Director Predictive Analytics jobs? Cities in Utah with the most Director Predictive Analytics job openings:

Senior Data Analyst - Fraud Strategy & Operations

Raisin

Lehi, UT โ€ข Hybrid

$80K - $101K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 24 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 Data Analyst - Fraud Strategy & Operations, 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.ย 
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.