- Location
- Germany; Ireland; London; United Kingdom
- Workplace
- Remote
- Department
- Data Science
- Education
- PhD
- Source
- Greenhouse
Description
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
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!
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:
2024 Best Workplaces for Women and in Canada by Great Place to Work®
To learn more about our privacy practices, please see our Privacy Policy.
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Skills
Machine LearningData Science
