Return to site

Hiring: Data Scientist

This is a fantastic opportunity for a Data Scientist with a statistical analysis background to contribute to building a data-enabled technology platform for the automotive wholesale industry.

Signal Automotive has created a streamlined end-to-end workflow platform and inventory management tool to scale its wholesale business and ecosystem. We are now focused on using AI/ML to better understand the complex market dynamics in the US auto industry. We have made solid progress here, and a common refrain from customers is ‘Signal knows my business better than I do’. 

You will work with truly awesome Business and Technology teams and will play a key role in helping discover the information hidden in vast amounts of data. Your primary focus will be on applying data mining techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products. We believe that data intelligence is a key component in transforming the automotive wholesale industry.

Our office is in Vilnius, Lithuania, but part and full-time remote is possible.

As a Data Scientist at Signal Automotive, you will:

  • Understand business objectives and develop models that help to achieve them, along with metrics to track their progress

  • Analyse the ML algorithms that could be used to solve a given problem and rank them by their success probability

  • Explore and visualise data to gain an understanding of it, then identify differences in data distribution that could affect performance when deploying the model in the real world

  • Data-mine using state-of-the-art methods, verify data quality, and ensure it via data cleaning

  • Find available datasets online that could be used for training, extend the company’s data with third-party sources of information

  • Define the preprocessing or feature engineer on a given dataset

  • Train models and tune their hyper parameters

  • Analyse errors of the model and design strategies to overcome them

  • Select features, build and optimise classifiers using machine learning techniques

  • Enhance data collection procedures to include information that is relevant for building analytic systems

  • Perform ad-hoc analysis and present results in a clear manner

  • Keep up-to-date on the trends of Automotive Wholesale and data in the space to facilitate innovation

Preferred candidates have:

  • Applied statistics skills, such as distributions, statistical testing, regression, etc.

  • Excellent understanding of machine learning techniques and algorithms

  • Expertise in visualising and manipulating big datasets (we use Big Query with SQL)

  • Experience with one or more of the following:

    • Forecasting for time series

    • Modeling intermittent and seasonal patterns such as customer demand

    • Graphical models e.g. Bayesian networks

  • Excellent teamwork skills

  • University degree

  • Very comfortable with English

For this role, data skills are preferred over software development skills, but here are some nice-to-haves:

  • Proficiency with Python and basic libraries for machine learning

  • Proficiency with SQL

  • Familiarity with Linux

  • Familiarity with processes and technical vocabulary working with Agile software teams

  • Experience with data flow management (e.g. Apache Airflow)

We offer:

  • Office for whenever needed in Vilnius Old Town with a parking

  • Flexible working hours

  • Private benefit for learning and training

  • Medical Insurance benefits

  • Gross monthly salary: from €2,300 based on the skills and experience

If this opportunity excites you - we would love to tell you more.

All applications are kept confidential. Please submit a resume and an optional cover letter (we know it is old school, but if you have inspiration writing it we would love to hear it) telling us about your qualifications and motivation, plus any other information you feel would be relevant to Adroiti.

Please send us a note to people(at)adroiti.com and we'll get back to you quickly.

All Posts
×

Almost done…

We just sent you an email. Please click the link in the email to confirm your subscription!

OK