Posted 25 Aug 2026 (71 days ago) · Job 8864 · Read from the employer's Greenhouse board, last checked 5 Nov 2026, 16:25 UTC

Director of Data Science & Analytics

Everlane · Los Angeles, California

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What the posting says

Each fact carries its state:Statedfound in the postingConflictstwo statements disagree, both quotedNot mentionedthe posting does not say

PayStated
$170,000–$200,000 a year
Employment typeStated
Full time
ExperienceStated
10+ years
EducationStated
['bachelor degree']

Not mentioned in this posting

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Work arrangementNot mentioned
The posting does not say
ShiftNot mentioned
The posting does not say
Visa sponsorshipNot mentioned
The posting does not say

Requirements, each with its sentence from the posting

These are the employer’s words. The index does not judge whether you meet them.

  • BA/BS in business analysis, quantitative or computing fieldrequired

    BA/BS degree in business analysis, quantitative or computing focused degreefrom the posting

  • 7+ years retail/e-commerce or B2C technology experiencerequired

    7+ years of experience in retail/e-commerce or a B2C technology companyfrom the posting

  • 5+ years data technology experiencerequired

    5+ years of data technology experience (data collection, analysis, machine learning, statistical modeling)from the posting

  • 3+ years people managementrequired

    3+ years of people management experiencefrom the posting

  • Pythonrequired

    Expertise in R, Python, or another data science suitable languagefrom the posting

  • Rrequired

    Expertise in R, Python, or another data science suitable languagefrom the posting

  • SQLrequired

    Expertise in SQLfrom the posting

  • Statistics and probabilityrequired

    Strong fundamentals in statistics and probability, including formal statistical modeling and experimental designfrom the posting

  • Machine learningrequired

    5+ years of data technology experience (data collection, analysis, machine learning, statistical modeling)from the posting

  • Experimental designrequired

    Strong fundamentals in statistics and probability, including formal statistical modeling and experimental designfrom the posting

Read the full posting as the employer wrote it

Clean luxury. Better for you. At Everlane, we believe luxury should be as effortless as it is conscious. We partner with ethical factories, work with premium, sustainably sourced materials, and strive to leave the industry cleaner than we found it. There's still much to do, and we're excited to grow a team of motivated humans ready for the challenge. The journey toward better continues.

Everlane is seeking a Director of Data Science & Analytics to join our team, where you’ll help drive growth of the Everlane business by leading a team that collaborates with business partners to provide meaningful insights and analysis for critical business decisions, develops reporting, analytics and predictive models, and builds the next generation of Everlane’s data infrastructure. The subject areas that you will impact span the entire company, from analyzing performance marketing data for optimization and helping our digital product team evaluate new opportunities of improvement on our website, to building a model around the purchase preferences of our customers. This position reports into the VP of Digital.

Our team is tasked with building actionable insights from our data, building predictive data products, and creating self-service analytical tools for teams throughout the company.  We use a full-stack set of methodologies to achieve this, taking a data science problem from the initial open ended business question, to the eventual productionisation and implementation of a model.

Your day-to-day:

  • Effectively communicate and drive collaboration with key stakeholders across the business to provide insights, analysis and recommendations
  • Own the Data architecture and roadmap, working independently to understand, prioritize, and plan the team’s work
  • Research and promote opportunities to take on new technologies, frameworks, and approaches in customer data analysis, AB testing, data and machine learning
  • Apply causal research and explanatory modeling to better understand customer behavior, marketing performance, site behavior, etc.
  • Deploy predictive data models that our customers will interact with, including product recommendations, size predictions, and predicted return rates
  • Design and analyze rigorous experiments aimed at understanding customer behavior
  • Scale the Everlane data platform with smarter and more sophisticated data on ongoing basis
  • Oversee a skilled team of data analysts, data scientists, and data engineers, coaching direct reports and developing their skills

We'd love to hear from you if you have:

  • BA/BS degree in business analysis, quantitative or computing focused degree
  • 7+ years of experience in retail/e-commerce or a B2C technology company
  • 5+ years of data technology experience (data collection, analysis, machine learning, statistical modeling)
  • 3+ years of people management experience
  • Ability to understand and interpret the business and provide a firm point of view from both a stakeholder and data perspective
  • Expertise in R, Python, or another data science suitable language
  • Expertise in SQL
  • Strong fundamentals in statistics and probability, including formal statistical modeling and experimental design

 



The Fine Print:

 

LA: This is a full-time role based in our Los Angeles Creative Studio located in the Arts District. We are on a hybrid schedule, with at least three days in the office per week, Tuesdays through Thursdays.

 

California Residents:  At Everlane, we carefully consider a wide range of compensation factors, including your background and experience. These considerations can cause your compensation to vary. The annual compensation range for this role is $170,000 - $200,,000. This range is based on the Los Angeles geographic area and the actual pay may vary depending on your skills, qualifications, experience, and geographic location. 

 

Everlane is deeply committed to respecting and protecting your data privacy. For information on our privacy practices, please review our Privacy Policy.

The posting text is reproduced as the employer wrote it; the index adds nothing to it.