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Director Data Science Jobs in Layton, UT (NOW HIRING)

University of Utah

Data Scientists

Salt Lake City, UT · On-site

$75K - $105K/yr

Conducts work assignments as directed. Closely supervised with little latitude for independent ... P16 Data Scientist, II Produce innovative solutions driven by exploratory data analysis from ...

University Of Utah

Data Scientists

Salt Lake City, UT · On-site

Conducts work assignments as directed. Closely supervised with little latitude for independent ... P16 Data Scientist, II Produce innovative solutions driven by exploratory data analysis from ...

Omnicom

Data Analyst

Salt Lake City, UT · On-site

Data Science and Analytics MRM is part of the Omnicom Precision Marketing activation practice. This ... days are directed by their agency or manager. Our objective is to increase this requirement ...

AVA Consulting

Data Analyst

Salt Lake City, UT · On-site

You will partner directly with the Director of Executive and Equity Compensation to turn complex ... data science, finance, consulting, HR analytics, compensation, or a related field. You are a ...

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Director Data Science information

See Layton, UT salary details

$49.1K

$140.7K

$221.7K

How much do director data science jobs pay per year?

As of Aug 17, 2026, the average yearly pay for director data science in Layton, UT is $140,712.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,900.00 and $172,200.00 per year, depending on experience, location, and employer.

What is a director data science?

A Director of Data Science leads a team of data scientists and analysts to drive data-driven decision-making within an organization. They develop strategic initiatives, oversee machine learning and analytics projects, and collaborate with executives to align data efforts with business goals. The role requires expertise in data science, leadership, and communication to translate complex insights into actionable strategies.

What types of teams and professionals will I collaborate with as a director data science?

As a Director Data Science, you will regularly collaborate with cross-functional teams including business analysts, data engineers, software developers, product managers, and senior executives. Your role often involves translating business goals into data-driven strategies, as well as mentoring and guiding data scientists and analysts on your team. You may also work closely with stakeholders from marketing, operations, and finance to align analytics initiatives with organizational objectives. This collaborative environment fosters innovative solutions and ensures data science efforts have a meaningful impact on overall business performance.

What are the key skills and qualifications needed to thrive in the director data science position, and why are they important?

To thrive as a Director Data Science, you need a deep understanding of advanced statistical modeling, machine learning, and data strategy, typically backed by an advanced degree in a quantitative field and significant leadership experience. Proficiency with tools such as Python, R, SQL, cloud data platforms, and familiarity with data governance frameworks and certifications like Certified Analytics Professional (CAP) are common requirements. Outstanding communication, stakeholder management, and team leadership abilities make candidates stand out in this position. These skills ensure the successful translation of complex data insights into actionable business strategies and the effective leadership of high-performing data science teams.

What cities near Layton, UT are hiring for Director Data Science jobs?

Cities near Layton, UT with the most Director Data Science job openings:

Director Data Science jobs near you
Infographic showing various Director Data Science job openings in Layton, UT as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $140,712 per year, or $67.7 per hour.

Staff Data Scientist- Pricing Science

CSC Generation

Salt Lake City, UT • Remote

Full-time

Re-posted 17 days ago

Job description

CSC Generation is the AI-native holding company re-engineering omnichannel retail. We acquire iconic brands and transform them with Genesis, our operating platform combining a Data Fabric, Automation Engine, proprietary tools, and shared services to modernize operations, elevate customer experience, and expand margins. With $1B+ in revenue across 13 brands, our portfolio includes Sur La Table, Backcountry, One Kings Lane, and others that serve as real-world innovation labs.
 
Reports to: Director of Finance and Business Intelligence
Location: Remote — US or Canada
About the Role
As our Staff Data Scientist, you will design and ship production pricing systems such as demand forecasting, price elasticity modeling, dynamic pricing and the experimentation infrastructure needed to measure whether they actually work.
 
This is a hard, high-stakes problem: your models will directly influence margin and revenue decisions across a portfolio of brands operating at scale. You will own the full arc from framing ambiguous business problems as well-defined ML tasks through to monitoring models that hold up in production.
 
At six months, success looks like at least one pricing model shipped to production with measurable business impact and an experimentation framework in place that your stakeholders trust. If you have spent time building pricing systems from the ground up, not just consuming them, and you care deeply about rigorous causal inference and honest model evaluation, this role was written for you.
What You'll Do
  • Design and build production ML systems for pricing, demand forecasting, and related revenue problems
  • Frame ambiguous business problems as well-defined ML tasks with clear success criteria and measurable outcomes
  • Set the standard for model evaluation, validation, and monitoring — including knowing when CV metrics are misleading and when holdout testing is the only honest answer
  • Build robust predictive models across classification, regression, time series, and causal inference
  • Identify and prevent data leakage, overfitting, and other failure modes before they reach production
  • Design and analyze experiments to measure causal impact of pricing decisions
  • Debug models that fail in production — understand why they fail, not just that they do
  • Translate model limitations, uncertainty, and risk clearly to both technical and non-technical stakeholders
  • Partner with product, engineering, and business teams to ensure ML solutions solve real problems
Required Qualifications
  • 7+ years of applied ML / data science experience with a track record of production systems that delivered measurable business impact.
  • Deep experience in pricing, demand forecasting, or revenue optimization — you have built these models end-to-end, not just consumed them.
  • Expert-level Python and SQL.
  • Deep understanding of ML fundamentals beyond API-level usage, including model evaluation, validation, and failure mode diagnosis.
  • Strong grounding in causal inference and experimental design, including the ability to distinguish correlation from causal result.
  • Ability to work with messy, real-world data and make pragmatic tradeoffs under ambiguity.
  • Familiarity with cloud ML platforms (GCP/Vertex AI or AWS/SageMaker).
  • MS or PhD in Statistics, Computer Science, Operations Research, or a related quantitative field.
Preferred Qualifications
  • Experience in e-commerce, retail, marketplace, or pricing-intensive industries such as airlines, ride-sharing, or fintech.
Why Join
The people who do best here are builders. They take ownership, move fast, and want to see the direct impact of their work.
  • Portfolio-Level Impact: Your models will influence pricing and margin decisions across a $1B+ portfolio of brands — the output of your work is visible at the executive level from day one.
  • AI-First Skill Building: Get hands-on with production ML infrastructure, causal inference at scale, and the Genesis platform — building a modern, applied ML skill set on real retail data problems.
  • Ownership: You will own the full problem from framing through production, with the autonomy to make technical decisions and the stakeholder access to see them through.
  • Competitive Benefits (CAN): Comprehensive benefits including paid time off, RRSP match, group benefits, and employee discounts across portfolio brands.
  • Competitive Benefits (US): Comprehensive benefits including paid time off, 401(k) match, medical, dental, vision, supplemental coverage, and employee discounts across portfolio brands.
Interview Process
  1. Recruiter Screen: 30-minute call to cover your background, the role, and logistics.
  2. Hiring Manager Interview: Conversation with the Director of Finance and Business Intelligence focused on your pricing science experience, approach to ambiguous ML problems, and how you've driven production impact.
  3. Technical / Case Discussion: Deep dive into a pricing or demand forecasting problem — expect questions on model evaluation, causal inference, and production failure modes. Cross-functional stakeholders may join.
  4. Executive Interview: Final conversation with senior leadership.
  5. Reference Checks: Conducted in parallel with the final stages where possible.
  6. Offer: We move quickly for the right candidate.
For US-based candidates, this posting is intended for candidates that reside in the following states:
AZ, DE, FL, GA, IN, LA, MI, MS, MO, NV, NC, OK, PA, TN, TX, UT, WV, WI, and WY.
 
For Ontario applicants, please note that this posting is for an existing vacancy.
 
The CSC Generation family of brands provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, provincial, state or local laws. 
 
The CSC Generation family of brands is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact hrbenefits@cscshared.com.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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About CSC Generation

Sourced by ZipRecruiter

CSC Generation is a multi-brand technology platform based in Merrillville, IN, United States. The organization operates in the retail sector and utilizes technology to save retail companies from going into bankruptcy, while also offering consumers the ability to lease their purchases. Founded by serial entrepreneur, Justin Yoshimura, CSC Generation has leveraged its proprietary technology and customer database to quickly revitalize distressed retail brands. The company's mission revolves around the concepts of reinvention and innovation as it aims to redefine traditional retail and direct-to-consumer models in today's digital age. Notably, the company has, to date, acquired several brands such as DirectBuy, Killion, and most notably, Z Gallerie, growing fast within the e-commerce sector.

Company size

501 - 1,000 Employees

Headquarters location

Merrillville, IN, US

Year founded

2016

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