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Staff Data Scientist, Investment Modelling

unlimited holidays - extra holidays - extra parental leave - long remote period allowed

Remote:

Hybrid

Contract:

Full time

Experience:

Senior (5-10 years)

Work from:

Tallinn (EE)

Offer summary

Qualifications:

At least 5 years of experience in Data Science and Machine Learning., Expertise in Timeseries Forecasting, financial metrics forecasting, and budget modelling., Proficient in Python and relevant libraries., Experience in statistical hypothesis testing., PhD in a quantitative discipline is a plus..

Key responsabilities:

Develop and maintain forecasting models improving business growth accuracy.
Deploy statistical models using AWS and ML platforms with Python.
Solve optimization challenges to maximize ROI from incentives.
Communicate model outcomes effectively to stakeholders.
Collaborate with cross-functional teams for business insights.

Bolt Fintech: Finance + Technology Unicorn https://bolt.eu/

1001 - 5000 Employees

HQ: Tallinn

See more Bolt offers

Job description

<gh-intro>
<text>

We’re looking for an experienced Staff Data Scientist to join our Investment Modelling team. The role focuses on building quantitative growth models and optimising investments across hundreds of cities worldwide!</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 50+ 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>

As a Staff Data Scientist, you’ll develop forecasting models to predict the short- and long-term impact of incentives on business growth. You’ll also use optimization techniques to distribute incentives over different periods, cities, and channels to maximise business growth.

You’ll be responsible for building products powered by Data Science models that internal teams can use for portfolio planning and budgeting. In addition, you’ll work on decomposing and modelling business growth into interpretable and actionable components.

As a Staff level Data Scientist, you will coach less experienced team members by sharing good practices in problem-solving, modelling, software engineering and soft skills.

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

<gh-responsibilities>

<title>Main Tasks and Responsibilities:</title>

<point>Utilising advanced forecasting methods to design, develop, and maintain model frameworks across multiple business verticals for short- and long-term horizons, ensuring high accuracy and low operational cost.</point>
<point>Rapidly deploying models to production with AWS and internal ML platforms and working with Python, Spark, Presto, Docker, SageMaker, Airflow tech stack.</point>
<point>Solving complex optimisation problems by simulating strategic solutions for incentives budget allocation while balancing local and global constraints to maximise ROI.</point>
<point>Effectively communicating model outcomes as insights to a diverse group of stakeholders.</point>
<point>Working in cross-functional teams with Data Analysts, Data Scientists, Product Managers and Software Engineers to gain a deep understanding of technical and business needs.</point>
<point>Regularly share knowledge with other Data Scientists across all seniority levels, promoting learning and innovation in a collaborative environment.</point>

</bulletpoints>
</gh-responsibilities>

<gh-requirements>

<title>About you:</title>

<point>You have at least 5 years of experience in Data Science and Machine Learning, ideally in product development within a technology-focused company.</point>
<point>You are experienced in Timeseries Forecasting, specifically financial metrics in marketplaces, scenario-based forecasting, capital allocation and budget modelling.</point>
<point>You apply first-principle thinking to break down complex challenges and design innovative solutions from fundamental concepts.</point>
<point>You’re skilled in Python programming, libraries such as Pandas, Numpy, scikit-learn, and OR-tools for data analysis and modelling, with practical experience in statistical hypothesis testing that allows you to independently identify problems, explore trends, and discover opportunities through data-driven methods.</point>
<point>You exhibit excellent teamwork and strong communication skills in English, both verbal and written, enabling clear collaboration and knowledge-sharing.</point>
<point>You’ll get bonus points if you have a PhD in a quantitative discipline such as Physics, Mathematics, Computer Science, or Economics, showcasing the ability to translate data insights into impactful products and demonstrating deep analytical and research capabilities.</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 600+ cities across 50+ 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 with a minimum of 2 days in the office each week to foster strong connections and teamwork.</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 and role.</text>
</gh-perks>

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