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Senior Data Scientist / Staff Data Scientist

StackAdapt

Full-time
Germany
machine learning
data science
computer science
statistics
tech
Apply for this position

StackAdapt is a self-serve advertising platform that specializes in multi-channel solutions including native, display, video, connected TV, audio, in-game, and digital out-of-home ads. We empower hundreds of digitally-focused companies to deliver outcomes and exceptional campaign performance everyday. StackAdapt was founded with a vision to be more than an advertising platform, it’s a hub of innovation, imagination and creativity.

We are searching for a talented senior level Data 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 Germanyf 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

StackAdapters enjoy:

  • Competitive salary

  • Private Medical Insurance cover

  • Auto-enrolment into the company pension scheme

  • Work from home reimbursements

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

  • An awesome parental leave policy

  • A friendly, welcoming, and supportive culture

  • Our social and team events (virtually!)

  • Take part in our walk and wander policy and work anywhere in the world for up to 90 days a year

If this role speaks to you then please submit an application - we'd love to speak with you. Due to a high volume of interest, only those shortlisted for interview will be contacted.

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

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About the job

Full-time
Germany
26 Applicants
Posted 3 weeks ago
machine learning
data science
computer science
statistics
tech

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Senior Data Scientist / Staff Data Scientist

StackAdapt

StackAdapt is a self-serve advertising platform that specializes in multi-channel solutions including native, display, video, connected TV, audio, in-game, and digital out-of-home ads. We empower hundreds of digitally-focused companies to deliver outcomes and exceptional campaign performance everyday. StackAdapt was founded with a vision to be more than an advertising platform, it’s a hub of innovation, imagination and creativity.

We are searching for a talented senior level Data 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 Germanyf 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

StackAdapters enjoy:

  • Competitive salary

  • Private Medical Insurance cover

  • Auto-enrolment into the company pension scheme

  • Work from home reimbursements

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

  • An awesome parental leave policy

  • A friendly, welcoming, and supportive culture

  • Our social and team events (virtually!)

  • Take part in our walk and wander policy and work anywhere in the world for up to 90 days a year

If this role speaks to you then please submit an application - we'd love to speak with you. Due to a high volume of interest, only those shortlisted for interview will be contacted.

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

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