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Senior Data Scientist, Campaigns

unlimited holidays - extra holidays - extra parental leave - long remote period allowed
Remote: 
Hybrid
Contract: 
Experience: 
Mid-level (2-5 years)
Work from: 
Tallinn (EE)

Offer summary

Qualifications:

4+ years industry experience in data science and machine learning, Strong skills in statistics, probability, causal inference, and SQL, Experience deploying models to production and conducting A/B tests.

Key responsabilities:

  • Build ML models for user behavior prediction and segmentation
  • Automate promo campaign distribution and optimize discount allocation
  • Design experiments, study historical data, and compare campaign methodologies
  • Collaborate with cross-functional teams on campaign features and setups
Bolt logo
Bolt Fintech: Finance + Technology Unicorn https://bolt.eu/
1001 - 5000 Employees
HQ: Tallinn
See more Bolt offers

Job description

<gh-intro>
<text>

We are looking for an experienced Senior Data Scientist to help us improve Bolt’s Campaigns </text>
</gh-intro>

 

<gh-about-us>
<title>About us</title>

<text>

Bolt is one of the fastest-growing tech companies in Europe and Africa, with over 150 million customers in 45+ countries. We’re a global team of more than 100 nationalities joined on a common mission – to make cities for people, not cars. And we need you to make it happen!

</text>

</gh-about-us>

<gh-role-detail>

<title>About the role</title>

<text>

You will be building models for predicting user and market behaviour under different circumstances, such as incentives, competitors' activity, and seasonality. You will work on customer segmentation: discover rider, driver, and eater segments for efficient campaign targeting. As a Data Scientist, you will be developing a system for automating promo campaigns distribution and scaling it for millions of Bolt customers. You will be engaged in designing optimal experimental setup for comparing different campaigns targeting methodologies and user behavior dynamics. You will work on uplift modelling topics to help shaping the most efficient campaign offerings.

</text>
</gh-role-detail>

 <gh-responsibilities>

<title>Your daily adventures will include:</title>

<bulletpoints>

  • <point> Machine learning and statistical model development and its deployment into a production environment </point>
  • <point> Setting up A/B tests, collecting, interpreting its results and communicating to stakeholders </point>
  • <point> Working closely with the Experimentation team to figure out robust design of campaigns experiments </point>
  • <point> Studying historical user behaviour data to identify opportunities for optimisation </point>
  • <point> Building models for optimal users’ discount allocation </point>
  • <point> Developing a system for automating regular promo campaign setups  </point>
  • <point> Working with a technical stack consisting of Python, Docker, Presto, SageMaker, Airflow </point>
  • <point>Collaborating with data analysts, data scientists, product managers and software engineers in feature teams </point>

</bulletpoints>
</gh-responsibilities>

<gh-requirements>

<title>About you:</title>

<bulletpoints>

  • <point>Industry experience in data science and machine learning (4+ years recommended) </point>
  • <point>Practical experience setting A/B tests and interpreting results  </point>
  • <point>Deep understanding the theory behind statistical hypothesis testing  </point>
  • <point>Profound knowledge of statistics, probability, and causal inference  </point>
  • <point>Track record of deploying models to production and measuring the impact  </point>
  • <point>Strong product thinking, ability to communicate and persuade, problem-solving  </point>
  • <point>Experience writing complex SQL queries  </point>
  • <point>Ability to map business and product problems on data science framework  </point>
  • <point>Proactive mindset, willingness to take initiative and work with little supervision  </point>
  • <point>Team player with excellent communication skills  </point>
  • <point>You will get extra credits for experience in modelling and successful implementation of causal inference </point>
  • <point>You will get extra credits for Ph.D. in Computer Science, statistics, or related quantitative fields, or a Master's degree with equivalent industry experience </point>
  • <point>You will get extra credits for a background in econometrics, operations research, simulation or quantitative analysis of behaviour </point>

</bulletpoints>

<text>

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying if you feel you’re the kind of person described above!
</text>
</gh-requirements>

<gh-perks>

<title>Why you’ll love it here:</title>

<bulletpoints>

  • <point>Play a direct role in shaping the future of mobility.</point>
  • <point>Impact millions of customers and partners in 500+ cities across 45 countries.</point>
  • <point>Work in fast-moving autonomous teams with some of the smartest people in the world. </point>
  • <point>Accelerate your professional growth with unique career opportunities.</point>
  • <point>Get a rewarding salary and stock option package that lets you focus on doing your best work.</point>
  • <point>Enjoy the flexibility of working in a hybrid mode.</point>
  • <point>Take care of your physical and mental health with our wellness perks.</point>

</bulletpoints>
<text>*Some perks may differ depending on your location.</text>
</gh-perks>

#LI-Hybrid

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Industry :
Fintech: Finance + Technology
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Verbal Communication Skills
  • Open Mindset
  • Teamwork

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