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Director Predictive Analytics Jobs in Seattle, WA

Director, Software Engineering

Seattle, WA · On-site

$287K/yr

This positon is a apeople manager role reporting to the Senior Director, Software Engineering ... or predictive analytics * Experience improving the performance and reliability of large telemetry ...

Director, Software Engineering

Seattle, WA · Hybrid

$287K/yr

This positon is a apeople manager role reporting to the Senior Director, Software Engineering ... or predictive analytics * Experience improving the performance and reliability of large telemetry ...

Serve as a Subject Matter Expert (SME) in modeling, simulation, and predictive analytics to support ... Experience leading functional teams or technical projects, including direct customer/sponsor ...

Showing results 21-40

Director Predictive Analytics information

See Seattle, WA salary details

$114.4K

$151.2K

$182.1K

How much do director predictive analytics jobs pay per year?

As of Aug 21, 2026, the average yearly pay for director predictive analytics in Seattle, WA is $151,156.00, according to ZipRecruiter salary data. Most workers in this role earn between $140,000.00 and $161,000.00 per year, depending on experience, location, and employer.

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 key skills and qualifications needed to thrive as a director of predictive analytics?

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 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 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 cities near Seattle, WA are hiring for Director Predictive Analytics jobs?

Cities near Seattle, WA with the most Director Predictive Analytics job openings:

Director, Business Intelligence (Seattle)

Metropolis Technologies

Seattle, WA • On-site

Full-time

Medical, Life, Retirement

Posted 20 days ago


Job description

Who We Are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy - a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators, and problem solvers to help us create it.

Who You Are

Metropolis is seeking a Director, Business Intelligence – Finance to own the vision, strategy, and execution of Metropolis’s Business Intelligence function. You are an organizational architect with a track record of building high-performing, multi-disciplinary data teams from scratch - engineers, data scientists, and analysts - and shaping the data culture of the organizations you’ve led. You operate comfortably at the intersection of C-suite Finance strategy and hands‑on quantitative analysis - translating the CFO’s most pressing questions into a multi-year roadmap and the team to deliver it. You are a builder who thrives on complexity across systems, stakeholders, and business cycles, and who never loses sight of what matters most: trustworthy data and intelligence that drives better decisions, faster.

What You’ll Do
  • Own the Finance Business Intelligence strategy by setting the multi-year vision to build, govern, and scale the finance data environment from pipeline architecture to self‑serve analytics and board-level reporting
  • Hire and develop the function’s first BIEs, data scientists, and analysts, building toward a high-performing, multi-disciplinary team
  • Evolve Finance analytics from reporting to intelligence by developing predictive modeling, AI-powered anomaly detection, driver-based forecasting, and scenario simulation
  • Serve as the executive-level data partner to the Finance organization, translating strategic priorities into data infrastructure investments
  • Design and govern the intake, prioritization, and delivery framework for all Finance data work to operate as a high-velocity, trusted product team
  • Drive company-wide Finance data governance by establishing policies, standards, and ownership models that make metrics authoritative, discoverable, and auditable
  • Evaluate and select tools, platforms, and integrations for the Finance data stack in partnership with the CTO and Data Platform team
What we’re looking for
  • 10+ years in Data Engineering, Business Intelligence, Data Science, or Financial Technology, including 4+ years leading data teams and building organizations from the ground up, with a path to managing managers as the team scales
  • Track record of building and scaling a multi-disciplinary data function at a high-growth technology or operations-intensive company
  • Executive presence with fluent data storytelling skills to connect complex quantitative findings directly to business action
  • Technical foundation in the modern Finance data stack (Snowflake, dbt, Airflow, Spark, Looker/Tableau) and cloud platforms (AWS or GCP), alongside statistical modeling and predictive analytics fluency
  • Analytical depth and quantitative rigor in model validation, forecasting accuracy, statistical significance, and hypothesis-driven analysis
  • Proven ability to drive lasting data governance and quality programs across systems and business cycles
  • Track record of building AI/ML-augmented finance analytics including anomaly detection, intelligent forecasting, and automated variance analysis
While not required, these are a plus
  • BS/BA degree in Computer Science, Mathematics, Statistics, Economics, or a related quantitative field; advanced degree (MBA, MS, or PhD) in a quantitative discipline
  • Experience with ERP/EPM and FP&A planning tools (Oracle, NetSuite, Workday, Anaplan, Adaptive Insights, or Pigment) in a large-scale transformation context; familiarity with scripting and statistical tools beyond SQL - Python, R, or SAS - and comfort evaluating data science work product from senior ICs
  • Fluency in core Finance processes (AP, AR, GL, revenue recognition, close cycles, FP&A) and experience translating strategic Finance priorities into multi-year data roadmaps; experience designing experimentation and measurement frameworks - defining how a team validates its models, tests financial assumptions, and measures forecast accuracy
  • Background in multi-vertical or multi-entity Finance environments (parking, aviation, retail, or similar operational businesses)
  • Track record of building AI/ML-augmented finance analytics - anomaly detection, intelligent forecasting, automated variance analysis
4 Days in Office

Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows.

The anticipated base salary for this position is $190,000.00 USD to $260,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis' total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more.

Metropolis may utilize an automated employment decision tool (AEDT) to assess or evaluate your candidacy for employment or promotion. AEDTs are used to assist in assessing a candidate's application relative to the required job qualifications and responsibilities listed in the job posting.

As part of this process, Metropolis retains data relevant to your candidacy, including personal information, for a period that is reasonably necessary for the use of the tool. If you are hired for the position, your data may become part of your employee records.

Metropolis Technologies is an equal opportunity employer. We make all hiring decisions based on merit, qualifications, and business needs, without regard to race, color, religion, sex (including gender identity, sexual orientation, or pregnancy), national origin, disability, veteran status, or any other protected characteristic under federal, state, or local law.

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