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Data Scientist (ML Engineer)

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Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Build optimization systems that set bids and place spend autonomously for advertisers

  • Design and analyze experiments to derive actionable insights

  • Analyze advertising performance data to improve core bidding strategies

  • Decide where reinforcement learning, classical optimization, or LLM reasoning fit

From the employer’s posting
the system that sets bids and allocates spend in production, in real time, against each advertiser’s goals
Design, Implement, and Analyze experiments for deriving Actionable Insights.
Analyze advertising performance data to improve the core strategies that power Perpetua's advertising engine.
deciding where reinforcement learning and classical optimization are the right tools, and where LLM-based reasoning meaningfully improves how the platform plans and explains its decisions

Benefits in the posting

Full benefits wording
  • Competitive paid time off, including annual leave plus paid public holidays
  • Great learning and development opportunities

From the employer’s posting.

About Omnicom Group

Flywheel’s suite of digital commerce solutions accelerate growth across all major digital marketplaces for the world’s leading brands.

In the employer’s words · Read in context

Apply at Omnicom Group

Posting record

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Actively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 29, 20266 days ago
Recorded sightings
8
Last seen by us
Nov 4, 2026
Employer says posted
Jul 28, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 6

Similar jobs usually come down between day 6 and day 69.

From 4,296 similar postings that came down. Coming down is not always a hire.

Omnicom Group is hiring

150 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • BigQuery
  • Keras
  • pandas
  • PyTorch
  • XGBoost
  • GCP
  • scikit-learn
Where the posting names them
Perpetua is the retail media platform within the Flywheel Commerce Network, built for the challenger brand; the operator who cannot out spend the category leader and has to out execute instead. Advertisers set goals based on strategy and Perpetua’s always on optimization executes the tactics. As a Data Scientist (ML Engineer), on the Perpetua team, you will design, experiment with, and ship the machine learning systems that decide how thousands of brands spend their advertising budgets across retail media. This is the engine that takes autonomous action on the customer’s behalf. It is not a model that produces recommendations for someone else to act on, but the system that sets bids and allocates spend in production, in real time, against each advertiser’s goals. Your work runs live across thousands of customers worldwide. Our team primarily works with Python and the Google Cloud Platform suite of products like Cloud Run and Vertex AI to productize cutting-edge data features. We are currently working on developing a scalable advertising bidding platform that enables advertisers to implement custom and versatile bidding strategies including but not restricted to maximizing advertising sales, dominating top-of-search placements, optimizing for total sales, incremental sales, new-to-brand purchases, organic rank, etc. Increasingly, this work sits alongside a newer layer of generative and agentic AI; LLM-based reasoning that plans, explains, and reacts to natural language goals. Knowing where classical optimization is the right tool and where the generative layer adds leverage is part of the craft on this team. What You Will Do: Work across retail media (starting with Amazon) to understand the intricate relationships between bids, placement, conversion, and sales, and turn that understanding into systems that optimize advertising autonomously on the customer’s behalf. Design, Implement, and Analyze experiments for deriving Actionable Insights.
Competent in training and evaluating models using mainstream data science tools including but not limited to sklearn, Pandas, keras and/or PyTorch Experience in cloud native ML training platforms like BigQuery ML or Snowpark Working at Flywheel
Able to create and make changes to traditional ML models, including but not limited to Linear regression, XGBoost and Logistic regression Competent in training and evaluating models using mainstream data science tools including but not limited to sklearn, Pandas, keras and/or PyTorch Experience in cloud native ML training platforms like BigQuery ML or Snowpark
Curiosity about applied LLMs and agentic systems, and comfort using modern AI-assisted development tools (such as Claude Code) as part of how you build Able to create and make changes to traditional ML models, including but not limited to Linear regression, XGBoost and Logistic regression Competent in training and evaluating models using mainstream data science tools including but not limited to sklearn, Pandas, keras and/or PyTorch

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Agency:

Flywheel

Job Function:

Data and Analytics

Job Subfunction:

Data Engineering

Job Description:

About Flywheel  

Flywheel’s suite of digital commerce solutions accelerate growth across all major digital marketplaces for the world’s leading brands. We give clients access to near real-time performance measurement and improve sales, share, and profit. With teams across the Americas, Europe and APAC, we offer a career with real impact, endless growth opportunities and the support you need to be the best you can be. 

The Opportunity  

Perpetua is the retail media platform within the Flywheel Commerce Network, built for the challenger brand; the operator who cannot out spend the category leader and has to out execute instead. Advertisers set goals based on strategy and Perpetua’s always on optimization executes the tactics.  
As a Data Scientist (ML  Engineer), on the Perpetua team, you will design, experiment with, and ship the machine learning systems that decide how thousands of brands spend their advertising budgets across retail media. This is the engine that takes autonomous action on the customer’s behalf. It is not a model that produces recommendations for someone else to act on, but the system that sets bids and allocates spend in production, in real time, against each advertiser’s goals. Your work runs live across thousands of customers worldwide.  

Our team primarily works with Python and the Google Cloud Platform suite of products like Cloud Run and Vertex AI to productize cutting-edge data features. We are currently working on developing a scalable advertising bidding platform that enables advertisers to implement custom and versatile bidding strategies including but not restricted to maximizing advertising sales, dominating top-of-search placements, optimizing for total sales, incremental sales, new-to-brand purchases, organic rank, etc. Increasingly, this work sits alongside a newer layer of generative and agentic AI; LLM-based reasoning that plans, explains, and reacts to natural language goals. Knowing where classical optimization is the right tool and where the generative layer adds leverage is part of the craft on this team.  
 
What You Will Do: 
Work across retail media (starting with Amazon) to understand the intricate relationships between bids, placement, conversion, and sales, and turn that understanding into systems that optimize advertising autonomously on the customer’s behalf. 

Design, Implement, and Analyze experiments for deriving Actionable Insights. 

Analyze advertising performance data to improve the core strategies that power Perpetua's advertising engine. 

Help define how Perpetua’s machine-learning optimization works alongside the emerging generative and agentic layer, deciding where reinforcement learning and classical optimization are the right tools, and where LLM-based reasoning meaningfully improves how the platform plans and explains its decisions. 

Support the growth of the team by contributing to activities for establishing best practices, recruitment, and authoring design documents. 

 
Who You Are: 
5+ years of experience as a data scientist or engineer working with data scientists 

Strong experience with algorithms and data pipelines processing terabytes of data per day 

You have experience taking concepts from inception through to production and ongoing monitoring and enhancements 

Experience in retail media, digital advertising, or e-commerce is an asset 

You have worked in organizations with cross-functional teams of ~5 people, solving hard problems collaboratively and working tightly with your immediate team members and across the organization 

Working knowledge of reinforcement learning and linear/non-linear optimization is a strong asset, given how central these techniques are to the bidding engine 

Curiosity about applied LLMs and agentic systems, and comfort using modern AI-assisted development tools (such as Claude Code) as part of how you build 

Able to create and make changes to traditional ML models, including but not limited to Linear regression, XGBoost and Logistic regression 

Competent in training and evaluating models using mainstream data science tools including but not limited to sklearn, Pandas, keras and/or PyTorch 

Experience in cloud native ML training platforms like BigQuery ML or Snowpark 


Working at Flywheel

We are proud to offer all Flywheelers a competitive rewards package and unparalleled career growth opportunities and a supportive, fun and engaging culture.
We have office hubs across the globe where team members can go to feel productive, inspired, and connected to others - team members go into Hub Offices 3x a week

Competitive paid time off, including annual leave plus paid public holidays

Great learning and development opportunities

Benefits that help you live your best life

Parental leave and benefits

Volunteering opportunities

If you’re looking to connect with teammates on a topic of inclusion and identity, chances are there’s an ERG for that.

So you know: The hired candidate will be required to complete a background check

Learn more about us here: Life at Flywheel


The Interview Process:

Every role starts the same, an introductory call with someone from our Talent Acquisition team. We will be looking for company and values-fit as well as your professional experience; there may be some technical role-specific questions during this call.

Every role is different after the initial call, but you can expect to meet several people from the team 1:1 and there might be further skill assessments in the form of a Take Home Assignment/Case Study Presentation or Pair Programming/Live Coding exercise depending on the role. In your initial call, we will walk you through exactly what to expect the process to be.
 
Inclusive Workforce

Flywheel Commerce Network’s goal is to create a culture where all individuals of all backgrounds feel comfortable in bringing their authentic selves to work. We want all people to feel included and empowered to contribute fully to our vision and goals. Flywheel Commerce Network is an Equal Opportunity Employer and participates in E-Verify. All applicants will receive fair consideration for employment. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, marital status, gender identity, national origin, disability, or any other applicable legally protected characteristics in the location in which the candidate is applying.

If you have any accessibility requirements that would make you more comfortable during the application and interview process, please let us know at recruitment@flywheeldigital.com so that we can support you.

For more information about what data we collect and how we use it, please refer to our Privacy Policy.

We leverage AI technology to streamline our hiring workflow, though all candidate decisions are made by our Talent Acquisition Team. This position is for an existing vacancy.

IMPORTANT ALERT: Please beware of fraudulent job communications from individuals falsely claiming to be from Flywheel. We've identified fraudulent activity through social media and messaging services purporting to be from Flywheel requesting payments for job- and recruitment-related expenses. Flywheel never asks candidates for personal information such as bank account data or tax IDs nor payments via social media or chat-based applications. Report suspected fraud to local authorities immediately. To learn more, click here.

Please note,?we do not accept unsolicited resumes from 3rd party Recruitment Firms.

$120,000 - $140,000 CAD

Omnicom’s policy requires employees to work in the office for a minimum of three days a week, unless additional in-office days are directed by their agency or manager. Our objective is to increase this requirement over time, and many of our agencies as well as Omnicom’s corporate group already require five days of in-office attendance.


Omnicom is committed to hiring and developing exceptional talent. We agree that talent is uniquely distributed, and we’re focused on developing inclusive teams that can bring the best solutions to everything we do. We strongly believe that celebrating what makes us different makes us better together. Join us—we look forward to getting to know you. We will process your personal data in accordance with our Recruitment Privacy Notice.


Link to Recruitment Privacy Notice: https://www.omc.com/privacy-notice/

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