StackAdapt

Applied Machine Learning Scientist

Remote, United States remote Entry Salary not listed
remote Technology & IT Curated
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About the role

StackAdapt is the leading technology company that empowers marketers to reach, engage, and convert audiences with precision. With 465 billion automated optimizations per second, the AI-powered StackAdapt Marketing Platform seamlessly connects brand and performance marketing to drive measurable results across the entire customer journey. The most forward-thinking marketers choose StackAdapt to orchestrate high-impact campaigns across programmatic advertising and marketing channels.

We are searching for a talented Applied Machine Learning Scientist to join our engineering team as we continue to expand our data science efforts. Our platform is connected to thousands of publishers and advertisers worldwide and as a result, we're dealing with millions of requests each second, making billions of decisions. We utilize the latest technologies to solve challenges in traffic, data storage, machine learning, and scalability.

 

Want to learn more about our Data Science Team: https://alldus.com/ie/blog/podcasts/aiinaction-ned-dimitrov-stackadapt/

Learn more about our team culture here: https://www.stackadapt.com/careers/data-science 

Watch our talk at Amazon Tech Talks: https://www.youtube.com/watch?v=lRqu-a4gPuU

 

StackAdapt is a Remote First company, and we are open to candidates located anywhere in the UK, Ireland and Germany for this position.

What you'll be doing:

Innovate ML algorithms to maximize ROI and advertising performance. This ranges from creating entirely new algorithms, to improvements on state-of-the art methods, to development using a deep understanding of classic methods

Write production code, sometimes collaborating with Data Engineers, to implement the novel ML algorithms

Prototype potential algorithms and pipelines, test them using historical data, and iterate to modify based on insights

What you'll bring to the table:

Have a Masters degree or PhD in Computer Science, Statistics, Operations Research, or a related field, with dual degrees a plus.

Have the ability to take an ambiguously defined task, and break it down into actionable steps

Have a comprehensive understanding of statistics, optimization and machine learning

Are proficient in coding, data structures, and algorithms

Enjoy working in a friendly, collaborative environment with others

The compensation range listed for this role reflects the expected base salary for candidates located in the posting country based on a global rate. It is informed by market data and the approved budget for this position. StackAdapt maintains different compensation ranges for roles across other countries and regions, and final offers will be aligned to the candidate’s current location. We do not ask candidates about current or prior salary history, and we will not use such information, if volunteered, in setting an offer.

This range represents base salary only. Depending on the role, candidates may also be eligible for additional compensation such as annual bonuses, commissions, equity awards, and a comprehensive benefits package.

Factors Influencing Final Compensation:

The final compensation offer will be determined by a variety of factors, which may include, but are not limited to: the candidate's specific experience, technical skills, knowledge, abilities, and relevant education, licensure, and certifications.

Other business factors, such as organizational needs and budget alignment, may also be considered in the final offer.

Base Salary Band
€87.002—€119.627 EUR

StackAdapter's Enjoy:

Highly competitive salary

Retirement/ 401K/ Pension Savings globally

Competitive Paid time off packages including birthday's off!

Access to a comprehensive mental health care program

Health benefits from day one of employment

Work from home reimbursements

Optional global WeWork membership for those who want a change from their home office and hubs in London and Toronto

Robust training and onboarding program

Coverage and support of personal development initiatives (conferences, courses, books etc)

Access to StackAdapt programmatic courses and certifications to support continuous learning

An awesome parental leave program

A friendly, welcoming, and supportive culture

Our social and team events!

Please note: Benefits and perks may vary depending on your country of employment and the nature of your engagement. In locations where StackAdapt does not have a legal entity, employment and benefits are administered in accordance with local regulations and partner policies.

StackAdapt is a diverse and inclusive team of collaborative, hardworking individuals trying to make a dent in the universe. No matter who you are, where you are from, who you love, follow in faith, disability (or superpower) status, ethnicity, or the gender you identify with (if you’re comfortable, let us know your pronouns), you are welcome at StackAdapt. If you have any requests or requirements to support you throughout any part of the interview process, please let our Talent team know.

 

We use artificial intelligence (AI) to streamline the resume reviews of candidates and assess their fit based on the criteria outlined in the job posting. We do not use AI to make any final hiring or interview decisions.

 

About StackAdapt

 

We've been recognized for our diverse and supportive workplace, high performing campaigns, award-winning customer service, and innovation. We've been awarded:

 

G2 Top Software for 2026
2026 Best Workplaces™ for Young Talent and in Canada by Great Place to Work®
#1 DSP on G2 and leader in a number of categories including Cross-Channel Advertising

 

To learn more about our privacy practices, please see our Privacy Policy.

 

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Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Role
Technology & IT Customer Service Digital Marketing Figma Operations Remote Collaboration remote

Likely questions

  1. Tell us about work you have done that is close to the Applied Machine Learning Scientist role.
  2. How would you approach your first 30 days at StackAdapt?
  3. Which of Customer Service, Digital Marketing and Figma have you used recently, and what did it help you achieve?
  4. Describe a time you solved a problem without waiting to be told exactly what to do.
  5. How do you stay organised and communicate clearly when working remotely?

Prepare before the call

  • A recent example that proves your experience with Customer Service, Digital Marketing and Figma.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the Applied Machine Learning Scientist role because I can bring practical experience in Customer Service, Digital Marketing and Figma, learn the team quickly, and contribute to the outcomes StackAdapt needs from this hire.

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