Data Science Manager

Publiceringsdatum: 2025-07-23

Vill du arbeta inom yrken med teknisk inriktning-branschen? Letar du efter en chans att arbeta som dataingenjör på Tink AB? Nu är det möjligt. Tink AB söker en medarbetare på heltid som vill arbeta tills vidare. Kan det vara du?

Denna position är tillgänglig i Stockholm. Tink AB har just nu ett ledigt jobb som dataingenjör. Sista ansökningsdagen till jobbet som dataingenjör hos Tink AB är lördag den andra augusti 2025.


Jobbannons

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

We are looking for a Data Science Manager to join our our Data Science team at Tink - part of Visa Open Banking. The team is within the Banking and Lending Technology (BLT) area leverages machine learning technologies to enrich transaction data and develop our foundational models. We are looking for a passionate Data Scientist who will be instrumental in driving the next generation of banking and lending solutions. You will work with cutting-edge ML technologies, leveraging your expertise to extract structured information from transaction descriptions and deploy ML systems in high throughput environments. As a member of our team, you will:

  • Develop and implement machine learning models to enrich transaction data.
  • Work closely with our engineering team to integrate models into our MLOps pipeline using Kubeflow.
  • Train models on accelerated hardware like GPUs using PyTorch.
  • Deploy and scale ML systems using Nvidia Triton Inference server.
  • Collaborate with cross-functional teams to ensure our models meet business needs and performance standards.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Basic Qualifications

  • 5+ years of relevant work experience with a Bachelor’s Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD, OR 8+ years of relevant work experience.

Preferred Qualifications:

  • Master's Degree in Computer Science, Mathematics, Physics, or other quantitative field. 4-6 years of work experience, preferably from building products rather than internal analysis/support.
  • Fluent in Python and SQL (BigQuery).
  • Experience with Deep Learning frameworks, particularly PyTorch.
  • Experience working in an MLOps pipeline, preferably with Kubeflow.
  • Proven experience training models on accelerated hardware like GPUs.
  • Strong interest in Natural Language Processing (NLP) and algorithms.
  • Mastery of concepts related to time and memory complexity.
  • Interest in deploying ML systems in high throughput environments.

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Om jobbet

Antal tjänster1
ArbetstidHeltid
FöretagsnamnTink AB
LönFast månads- vecko- eller timlön
OmfattningTills vidare
Organisationsnummer5568982192
Typ av anställningVanlig anställning
YrkeDataingenjör
YrkesområdeYrken med teknisk inriktning

Ansökan

Tink AB söker en person till denna tjänst som dataingenjör med placerings i Stockholm. Om det låter intressant att arbeta som dataingenjör hos Tink AB skickar du in din ansökan senast 2025-08-02.

Källa: Arbetsförmedlingen

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