Lead Data Scientist

Posted 21 Days Ago
Hiring Remotely in United States
Remote or Hybrid
160K-170K Annually
Senior level
Artificial Intelligence • Automotive • Computer Vision • Information Technology • Internet of Things • Logistics • Software
We make a unified map designed for every moving vehicle
The Role
Lead evaluation and data strategy for advanced AI, vision, and perception systems. Define metrics, build evaluation frameworks, audit artifacts, prioritize fixes, and translate model behavior into product decisions and data-improvement loops to ensure production readiness and downstream usefulness.
Summary Generated by Built In
What's the role?

Advanced AI systems fail in ways that aggregate benchmarks often hide. HERE needs a technical leader who can determine whether models are accurate, robust, controllable and genuinely useful in downstream products.

You will lead evaluation and data strategy for AI, vision and perception systems. You will connect quantitative analysis, artifact review and real-world use cases to reveal failure modes, prioritize fixes and establish credible production-readiness standards.

Your work will shape what the team builds next, what data it needs and when a model is ready to move forward.

What will you do?
  • Define evaluation strategy, metrics, test sets and release gates for advanced AI, vision and perception capabilities.
  • Build reproducible evaluation pipelines across model quality, robustness, controllability, coverage and downstream utility.
  • Analyze model outputs and artifacts to identify failure patterns that summary metrics miss.
  • Translate model behavior into prioritized recommendations for model, data and product teams.
  • Design data-improvement loops, including dataset audits, gap analysis, sampling and targeted data acquisition or generation.
  • Partner with scientists and engineers on experiment design, benchmarking and statistically sound comparisons.
  • Communicate evidence clearly to technical leaders and product stakeholders, including tradeoffs and readiness decisions.
Who are you?

You are a rigorous applied scientist who can move between statistics, model behavior, data quality and product impact.

  • Strong experience evaluating machine-learning, computer-vision, multimodal or generative-AI systems.
  • Advanced Python and SQL skills with experience building scalable analysis or evaluation workflows.
  • Strong foundations in statistics, experimental design, error analysis and model validation.
  • Experience converting ambiguous quality questions into measurable criteria and actionable decisions.
  • Ability to inspect model outputs deeply, identify patterns and explain what should change next.
  • Technical leadership skills and the ability to influence across data science, engineering and product.
It would be great if you also bring
  • Experience with spatial, geospatial, sensor, map, trajectory or simulation data.
  • Experience evaluating generative models, temporal consistency or perception systems.
  • Familiarity with data-centric AI, active learning, synthetic data or human-evaluation programs.
  • Graduate degree in a quantitative or technical discipline

The expected base salary range for this position is $160,000 to $170,000 per year. Actual compensation will be based on factors such as skills and experience. This position is also eligible for an annual performance bonus, which is subject to company and individual performance. 

  

Life at HERE comes with generous benefits to support your health and overall wellness. Benefits available to US-based HERE employees include health (Medical/Dental/Vision) insurance, retirement savings plans, paid time off & leave policies.   

  

As part of HERE Technologies employment process, candidates will be required to successfully complete a background verification process. Offers of employment and any related claims are subject to the successful completion of a background verification. Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, HERE will consider for employment qualified applicants with arrest and conviction records. 

  

HERE is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, age, gender identity, sexual orientation, marital status, parental status, religion, sex, national origin, disability, veteran status, and other legally protected characteristics.  

  

Under Section 503 of the Rehabilitation Act of 1973 and VEVRAA, we have developed an affirmative action program (AAP) for individuals with disabilities and protected veterans. Portions of the AAP are available for review by applicants and employees through our People Team. 


#LI-REMOTE

Who are we?

HERE Technologies is a location data and technology platform company. We empower our customers to achieve better outcomes – from helping a city manage its infrastructure or a business optimize its assets to guiding drivers to their destination safely.


At HERE we take it upon ourselves to be the change we wish to see. We create solutions that fuel innovation, provide opportunity and foster inclusion to improve people’s lives. If you are inspired by an open world and driven to create positive change, join us. Learn more about us on our YouTube Channel.

Skills Required

  • Master's or PhD in Computer Science, AI, Machine Learning, or related field.
  • 5-8 years of experience in deep learning, computer vision, or multimodal AI.
  • Strong background in applied machine learning, computer vision, synthetic-data evaluation, or perception-system validation.
  • Experience designing metrics and evaluation frameworks for generative, simulation, or perception systems.
  • Experience connecting model behavior, data quality, and product outcomes in ambiguous AI systems.
  • Ability to translate research-quality experiments into practical engineering and release decisions.
  • Strong analytical judgment and clear written communication.
  • Comfort owning both strategy and execution in a small team.
  • Experience with simulation, autonomous systems, geospatial AI, or map-grounded perception tasks.
  • Familiarity with video quality metrics, structural similarity measures, temporal consistency checks, segmentation and detection evaluation, or label-quality assessment.
  • Experience assessing synthetic-to-real transfer, dataset usefulness for downstream models, data curation strategy, or production quality governance.

What the Team is Saying

Vrushali

HERE Technologies Compensation & Benefits Highlights

  • Healthcare Strength Health coverage is described as solid, with employer-verified medical, dental, vision, and mental-health/EAP resources. Public benefits materials consistently reference robust core coverage.
  • Leave & Time Off Breadth Vacation/PTO is employer-verified, and programs like sabbatical and volunteer time off are highlighted in company-facing summaries. These options indicate a broad time-off offering.
  • Flexible Benefits Work-from-home and hybrid arrangements are employer-verified, with many U.S. teams operating on a hybrid schedule. Flexibility features prominently in the total-rewards framing.

HERE Technologies Insights

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The Company
HQ: Amsterdam
6,000 Employees
Year Founded: 1985

What We Do

HERE Technologies is a location data and technology company that created the first digital map over 35 years ago. Today we are the world's leading location platform company with a global footprint across 52 countries. Although our strongest presence is in the automotive industry, we also work with leading companies across a wide range of industries, including transport and logistics, mobility, manufacturing and retail and the public sector.

Why Work With Us

At HERE, we're always excited about discovering people who share our passion for building innovative solutions that make the world easier to navigate. We believe our success is powered by our team's diversity, creativity and collaboration and we're always looking for opportunities to grow it further.

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HERE Technologies Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site: 2 days a week
HQAmsterdam, NL
JP
Bangkok, TH
Bengaluru, IN
Berlin, DE
Burlington, MA
Chicago, IL
Eindhoven, NL
El Desagüe, MX
Frankfurt am Main, DE
Gurugram, IN
Hanyang, KR
Kraków, PL
London, GB
Melbourne, Victoria
Mumbai, IN
Navi Mumbai, IN
Paris, FR
São Paulo, BR
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