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onXmaps

Offline digital maps for outdoor recreation

Data Science Manager 3

Data SciencePosted on Nov 10
Full-timeUnited States

About the Job

Requirements

  • A master's degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative discipline, or equivalent experience demonstrating advanced technical and scientific expertise.
  • At least 8 years of experience in data science, machine learning, or advanced analytics, including at least 3 years managing and developing technical teams.
  • Demonstrated ability to lead, coach, and develop data scientists, set clear expectations, manage performance, and build teams that consistently deliver high-quality results.
  • Deep technical expertise in statistical modeling, machine learning, and experimental design, with strong hands-on Python and SQL skills and experience delivering models on cloud platforms.
  • Ability to independently frame ambiguous problems, design rigorous investigations, evaluate methodological trade-offs, and translate complex analyses into actionable customer or business outcomes.
  • Experience leading complex data science initiatives from research through delivery, making sound technical and prioritization decisions while navigating uncertainty, competing demands, and delivery risks.
  • Ability to influence stakeholders, resolve competing priorities, and build alignment around technical approaches and business outcomes.
  • Demonstrated ability to establish scientific rigor through thoughtful evaluation of data quality, bias, uncertainty, model performance, and research limitations.
  • Ability to evaluate and responsibly apply emerging technologies, including AI, to improve technical workflows and team effectiveness.
  • Ability to demonstrate onX's Company Values and a shared passion for them.
  • Permanent U.S. work authorization is required as a condition of employment.
  • Ability to travel quarterly for multiple days to a corporate office or other onX strategic location, such as a Basecamp.

Responsibilities

  • Personally design, implement, and evaluate sophisticated models and analyses to solve complex, often ambiguous customer and business problems, contributing deep technical expertise while advancing the team's scientific work.
  • Provide scientific and technical direction by applying sound judgment to problem framing, method selection, data quality, bias, leakage, and uncertainty; establish meaningful baselines and evaluation criteria; and strengthen the team's technical capabilities through code reviews and pairing.
  • Lead and develop a team of data scientists by setting clear expectations, providing coaching and feedback, managing performance, and building the technical judgment, stakeholder ownership, and capabilities needed for sustained team success.
  • Own and prioritize the Data Science team roadmap in partnership with the Director of Data and cross-functional stakeholders, making informed trade-offs across customer and business impact, technical feasibility, delivery capacity, and longer-term research opportunities.
  • Define clear objectives and success criteria for Data Science initiatives, using rigorous evaluation, meaningful baselines, and bounded experiments to assess opportunities, guide investment decisions, and measure outcomes.
  • Lead complex Data Science initiatives from research and exploration through production integration, evaluation, and ongoing support, establishing clear plans, navigating technical uncertainty, and proactively addressing risks and dependencies.
  • Build alignment across Product, Engineering, BI, and User Research, navigating competing priorities, resolving cross-functional challenges, and establishing clear expectations and accountability for shared outcomes.
  • Establish clear data contracts, acceptance criteria, and operational ownership while developing reusable, reproducible capabilities and communicating findings through prototypes and actionable recommendations, with appropriate privacy and access controls.
  • Identify opportunities to improve Data Science practices through experimentation and the responsible use of AI, helping the team evaluate new approaches, validate results, and adopt effective workflows that improve quality and efficiency.

Desired Qualifications

  • Experience with geospatial or temporal modeling, recommendation systems, or customer behavior analysis.
  • Experience with Google Cloud Platform, particularly BigQuery, Dataproc, or Vertex AI.
  • A PhD in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative discipline.
  • Experience evaluating AI-powered product features or developing reusable research and machine learning tools and frameworks.

About the Company

onXmaps

Offline digital maps for outdoor recreation

OnXmaps offers offline digital maps for outdoor enthusiasts, focusing on land ownership and public-land information for hunters, hikers, and off-roaders. The maps are downloaded and work without internet, showing land boundaries, points of interest, trails, and routes; customers can buy maps for a specific area or subscribe for unlimited access. The platform also includes extensive off-roading coverage and route-planning tools, set apart by content created with input from hunters and by offering offline usability and brand partnerships through pro deals. Its goal is to help users plan, navigate, and explore safely and efficiently while generating revenue from map sales, subscriptions, and partnerships.

Company size
501-1,000
Company stage
Series B
Total funding
$195.1M
Headquarters
Missoula, MT
Founded
2009

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