Senior/Staff Applied Machine Learning Scientist

Posted Yesterday
2 Locations
Remote
Senior level
AdTech • Marketing Tech
The Role
Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.
Summary Generated by Built In

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 Senior/Staff 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 US or Canada for this position.
What you'll be doing:
  • Lead the creation and optimization of advanced machine learning algorithms—from developing new methods to refining existing techniques—to enhance advertising effectiveness and ROI using deep ML expertise.
  • Own the end-to-end development of production-grade ML models: write efficient, scalable code and collaborate with Machine Learning Engineers to deploy and integrate algorithms into live systems.
  • Drive the prototyping and rigorous testing of innovative algorithms and data pipelines using historical data to validate performance and scalability; lead iterative improvements based on data-driven insights.
What you'll bring to the table:
  • 3+ years of industry experience
  • 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
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 platform
  • 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!
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.
 
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:
 
Ad Age Best Places to Work 2024
G2 Top Software and Top Marketing and Advertising Product for 2024
Campaign’s Best Places to Work 2023 for the UK
2024 Best Workplaces for Women and in Canada by Great Place to Work®
#1 DSP on G2 and leader in a number of categories including Cross-Channel Advertising
 
#LI-REMOTE

Top Skills

Algorithms
Data Science
Machine Learning
Python
Statistics
Am I A Good Fit?
beta
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company
HQ: Toronto, Ontario
371 Employees
Year Founded: 2013

What We Do

StackAdapt is a self-serve advertising platform that specializes in multi-channel solutions including native, display, video, connected TV and audio ads.

Similar Jobs

Coinbase Logo Coinbase

Software Engineer

Artificial Intelligence • Blockchain • Fintech • Financial Services • Cryptocurrency • NFT • Web3
Remote
Canada
4000 Employees
154K-154K Annually

Coinbase Logo Coinbase

Machine Learning Engineer

Artificial Intelligence • Blockchain • Fintech • Financial Services • Cryptocurrency • NFT • Web3
Remote
Canada
4000 Employees
218K-218K Annually

VelocityEHS Logo VelocityEHS

Manager, Sales

Cloud • Greentech • Social Impact • Software • Consulting
Remote
2 Locations
550 Employees
157K-245K Annually

ServiceNow Logo ServiceNow

Engagement Manager

Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Remote or Hybrid
Toronto, ON, CAN
27000 Employees

Similar Companies Hiring

Scrunch AI Thumbnail
Software • SEO • Marketing Tech • Information Technology • Artificial Intelligence
Salt Lake City, Utah
ClickMint Thumbnail
Marketing Tech • Generative AI • eCommerce • AdTech
Malibu, CA
7 Employees
PRIMA Thumbnail
Travel • Software • Marketing Tech • Hospitality • eCommerce
US
15 Employees

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account