How do you make our customers happy?
By ensuring advertisers reach real customers and understand the true value of their campaigns.
You will work at the intersection of fraud detection and attribution, analyzing large‑scale behavioral data, identifying sophisticated fraud patterns, and helping the organization interpret attribution data correctly. A key part of your work is explaining what the data can and cannot tell us, guiding product, PMs, and business partners toward decisions rooted in statistical rigor and sound reasoning. Your insights strengthen trust in our entire marketing & advertising ecosystem.
The biggest challenge
This role demands an unflinching commitment towards the realities of fraud detection and attribution modeling. You’ll face datasets that are messy, adversarial, and often riddled with bias—there are no shortcuts or easy answers. Every day brings new tactics from fraud actors and shifting market dynamics, requiring a commitment to transparency and rigorous analysis.
Complexity is the norm: distinguishing genuine customer behavior from noise or malicious signals is rarely straightforward. You’ll investigate bot activity, attack surfaces, and suspicious cohorts, and you’ll be expected to clearly articulate how attribution data should—and should not—be interpreted. Quantifying uncertainty, bias, and econometric effects is a central part of the job, as is validating hypotheses with statistical rigor and improving attribution logic using advanced modeling techniques.
Success in this role is rooted in analytical independence and a collaborative mindset. You’ll bridge gaps across teams, translating complex findings into actionable insights and fostering a culture of transparency and trust. Leadership here is demonstrated not by titles, but by the courage to confront complexity, communicate honestly, and drive principled decisions that shape our advertising ecosystem.
What you’ll do as Data Scientist
You provide the analytical depth and cross‑team influence needed to keep our platform safe and accurately measured. Fraud actors evolve rapidly, and attribution accuracy requires both mathematical skill and clear stakeholder guidance.
You will combine technical modeling with strong communication and organizational influence, helping teams understand how to interpret data, weigh model choices, and align around the right direction.
You shape both our fraud detection evolution and our attribution logic, not only through modeling but by driving the conversations that lead to the right strategic choices.
You’ll need to:
separate genuine customer behavior from malicious or noisy signals
investigate attack surfaces, bot behavior, and suspicious cohorts
quantify uncertainties, biases, and econometric effects
validate hypotheses using statistical reasoning
improve attribution logic using statistical, econometric, ML, or neural network techniques
guide PMs and business in understanding trade‑offs
choose between ML, econometric models, or neural networks — and articulate why
You’ll work closely with cross-functional teams including data science, product, engineering, and business stakeholders, acting as a key resource for fraud detection and attribution analytics.
Expect a blend of hands-on data analysis, model development, team meetings, and stakeholder presentations, with a focus on driving actionable insights and platform safety.
Why you can make a difference
You bring depth in statistics, econometrics, machine learning, and analytical investigation.
You are energized by:
exploring ambiguous or messy data,
reasoning economically about value, uncertainty, and incentives,
separating signal from noise,
guiding teams toward the right modeling choices,
and independently diving into large datasets to uncover actionable insights.
Your work directly influences platform trust, advertiser value measurement, and detection quality.
3 reasons why this is (not) for you
Switch to find out
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Uncertainty slows you down
You prefer stable, predictable datasets and aren’t comfortable with analytical uncertainty or behavioral noise.
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Works best with structured questions
You avoid collaborative, iterative investigation and would rather wait for someone else to define the problem fully.
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You work best in your silo
You’re not interested in influencing or guiding cross-functional teams toward the best analytical choices.
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Ambiguity energizes you
You get energy from solving ambiguous, high-stakes challenges and shaping analytical direction for others.
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You enjoy wrestling data (and usually win)
You love diving deep into messy, adversarial data using tools like SQL, BigQuery, and ML frameworks to surface actionable insights.
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You’re a cross‑team player
You communicate clearly and influence across teams—engineering, product, business—bringing people together to drive real results.
Where you’ll be working.
You’ll join the Reliable product group within Marketing & Advertising, working closely with Engineering, Product, Analytics and Business teams. The team serves as the primary ingestion point for interaction data in Marketing & Advertising, holding a business-critical role in ensuring transparency to our advertisers.
Overview of hard skills
To be successful in this role, you need:
Experience shaping analytical solutions and guiding organizational decision‑making
Strong skills in statistics and/or econometrics
Experience with ML (any framework) — anomaly detection, fraud detection, or adversarial modeling a plus
Familiarity with attribution modeling, causal inference, or bias‑correction techniques
Proficiency in SQL (BigQuery) and Python
Ability to explain data and modeling choices to non‑technical stakeholders
Strong communication and data visualization skills
Curiosity and passion for applied ML, adversarial thinking, and complex data challenges correction‑ techniques
Perks of having a blue heart
Discover all perks
Bonus
The bonus is calculated at the end of the year and we always end the year with a fun party!
On and off
At bol we understand like no other that you have to take care of yourself first, then your environment and then bol. In that order. Therefore, everyone at bol receives 29 days of vacation.
The culture and the office
Our colleagues work hard to make the daily lives of our customers easier and more fun. But of course, we do this in an inspiring and creative environment!
Your application process
Your application
We’ll review your application with care. We aim to get in touch with you as soon as possible.
First contact
We’ll contact you to walk you through the process and take the first step to set up an interview. And since we’re already talking: feel free to ask any questions you may have.
The assessment
We will ask you to take an online HR assessment and a technical assessment. We’ll also discuss the position and the team in depth.
First date
During this interview we’ll get to know each other. We want to find out more about you, your work experience and skills.
Is this love?
Two interviews are usually enough to see if it’s a match. And if you agree… well, it’s the beautiful beginning of your career at bol.
Any questions?
I'm Monika Myslinska, Recruiter at bol. Anything I can help you with regarding the Senior Data Scientist - Ad Fraud & Attribution vacancy?
Get in touch!
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