Senior Data Scientist/ Data Engineer

Job description

What you’ll do

  • Help to make location content best-in-class by advocating for and implementing changes to technology, process, tools, and systems.
  • Draw our strategy based on insights obtained by manipulating data from a huge variety of sources: system logs, satellite imagery, vertical imagery, street level imagery, GPS traces, etc. individually and by fusing several combinations of these sources
  • Use these sources individually or their combinations to predict various map features and attributes by training statistical models/ ML / AI models
  • State the quality level of our maps via statistical experiments that help us understand where we are and why, and deliver effective insights that help drive our map editing strategy
  • Develop processes and tools to monitor and analyze model performance and data accuracy
  • Collaborate with teams to bring synergy, with tools a communications channels that ensure transparency and knowledge sharing cross the company
  • Mentor/Coach/Guide team members aspire to become a Data Scientist
  • Productionizing, deploying, testing, and monitoring of machine learning models including exposing them as service
  • Dedicate part of your weekly schedule on research and development to acquire new skills, run your own experiments, …
  • Work in a mostly-remote and flexible way that will allow you find the perfect work-life balance

What you’ll need

  • Bachelor’s/Masters/PHD in Computer science, Mathematics, Statistics, or equivalent field and must have min. 6+ years of overall experience
  • Minimum 4-5 Years of experience working as a Data Scientist in deploying ML at scale in production
  • Strong level of proficiency in Python, Unix/Linux, and SQL
  • Experience working with Big Data technologies (e.g., Hadoop, Hive, Spark, Presto, S3)
  • Experience in slicing and dicing of large data sets to draw insights
  • Strong problem-solving skills
  • Excellent written, verbal and presentation skills, good at data storytelling
  • Good statistical knowledge and expertise in designing and testing experiments
  • Experience in various ML / AI techniques and frameworks
  • Good communications skills in English

As a plus:

  • Experience in deploying trained models for high scalability on public cloud platforms (AWS/Azure) using Dockers/Kubernetes
  • Active participation in competitions on a platform such as Kaggle
  • Knowledge and experience with using GIS tools for spatial data analysis.
  • Knowledge and experience on Webscrapping (e.g., scrapy, selenium)
  • Reporting and dashboarding tools: PowerBI, Tableau, R Shiny, Dash, …

Meet your team

Maps Analytics team is focused on creating efficient ways to state our map quality and drive insights to the map production teams that help the company evolve in a smart way.

What we offer

  • Competitive compensation package.
  • Work flexibility program (Working @ TomTom) - work from both home and the office!
  • Home office benefits, with a setup budget and a monthly allowance to support.
  • Chance to work abroad for 90-calendar days in select countries and states!
  • Holiday package that includes your birthday off and a volunteering day per year.
  • Bring your ideas and innovation to life during our Hackathon, DevDays, and more!
  • Take on learning opportunities – internal programs, O’Reilly and LinkedIn learning.
  • The opportunity to join one of the few top tech location specialists and have an impact on the future of mobility.
  • Be part of a supportive, inclusive, and global culture.

After you apply

1. First call: If your application matches the role, then it’s time to put a voice to the name! We’ll call you to set up an interview.

2. Online assessment: We’ll send you an assignment - use your expertise to show us what you’ve got.
3. First interview: In this interview, we want to know more about you – what excites you about location technology and how can you help us solve global challenges.
4. Second interview: We'll dive into your potential role, showing you how you’ll fit into your team and contribute to our vision.
5. The final decision: Cue the fireworks, because we’ll start the onboarding!

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