ING Tech Poland

Senior Data Scientist

ING Tech PolandO firmie

ING Tech Poland

Zajęcza 4

Warszawa

Senior Data Scientist
Location: Warszawa

Must have:

  • Your Data Science knowledge enables you to build analytics solutions for the mitigation of Financial Crime related risks.
  • You are willing and able to learn and to improve your technical- as well your interpersonal skills.
  • You are a creative and curious Data Scientist who is looking forward to work on a wide variety of Financial Economic Crime related problems.
  • You have a thorough understanding of the machine learning algorithms and tooling and are able to pass your knowledge to others.
  • You are proficient in coding and you are able to deliver production ready code.
  • Your communication skills enable you to work together with many different parties throughout our organization.
  • You are not shy to ask for help of other Data Scientists in the team, and you are happy to help them out by sharing your knowledge and capabilities. You are able and willing to guide junior Data Scientists and interns in their work; you also have experience doing so in your previous roles.
  • You are a team player who strikes effective balance between independence and acting in the interest of the team.
  • You are perseverant and you do not give up when a problem is hard; you know how to deal with set-backs.
  • Your enthusiasm is contagious and inspires others to act; your act sets an example for others.
  • MSc or PhD with excellent academic results in the field of Computer Science, Mathematics, Engineering, Econometrics or similar.
  • At least 6 years work related experience in a similar role and/or environment, including:
  • Machine Learning: Classification, Regression, Clustering, Unsupervised methods, Text Mining. You have an excellent understanding of Random Forests, Gradient Boosting, Neural Networks, Logistic Regression, SVM, KNN, K-Means, etc. Parametric and non-parametric statistics is a pre.
  • Programming Languages: Python and R. Scala is a pre.
  • Tools: Spark, Hadoop.
  • Database handling: SQL, Hive. Familiarity with Oracle, Netezza, HBase, Cassandra, Graph databases is a pre.
  • Visualisation tools: D3.js, Shiny, Angular.

Nice to have:

  • A background in anti-money laundering services or fraud.
  • You have extensive experience with stakeholder management from within data science projects.
  • Your enthusiasm is visible and you are good with mobilizing people for our data driven purpose.
  • You like working in cross-functional teams to realize an ambitious goal.
  • Experience with working in an agile/scrum way, but at least you should have a strong willingness to do so.
  • You have extensive experience with transforming data to added value for your stakeholders. You are able to see things from a different perspective and to make original solutions work in practice; when suitable you propose such endeavors to stakeholders.
  • You are able to see where ING can set further steps towards becoming a truly data driven bank. You’re always thinking one step ahead, for example in advising about the best way of implementation.

Scope of duties

60%
  - Creating innovative scalable data driven solutions in the space of Financial Crime
 
30%
  - Work with teams to implement these solution sacross the organization
 
10%
  - Work collaboratively with an extended group of stakeholders, including but not limited to Operations, Compliance, Engineering, Legal,Corporate Audit
 
contract of employment
type of contract
9:00 - 17:00
work hours
Zajęcza 4, Warszawa
this is the location of our office
We take care of:

Uprzejmie informujemy, iż skontaktujemy się z wybranymi kandydatami.

Jeżeli w przyszłości, chciałbyś/chciałabyś brać udział w innych rekrutacjach prowadzonych przez ING Business Shared Services B.V. sp. z o.o. Oddział w Polsce z siedzibą w Katowicach, potrzebujemy Twojej dodatkowej zgody:  „Wyrażam zgodę na przetwarzanie moich danych osobowych na potrzeby przeprowadzenia przyszłych rekrutacji.”

W przypadku wyrażenia zgody na przetwarzanie Twoich danych osobowych na potrzeby przyszłych rekrutacji informujemy, że będą one wykorzystywane przez okres 2 lat. Wszystkie informacje dotyczące przetwarzania Twoich danych osobowych znajdziesz tutaj.

Must have:

  • Your Data Science knowledge enables you to build analytics solutions for the mitigation of Financial Crime related risks.
  • You are willing and able to learn and to improve your technical- as well your interpersonal skills.
  • You are a creative and curious Data Scientist who is looking forward to work on a wide variety of Financial Economic Crime related problems.
  • You have a thorough understanding of the machine learning algorithms and tooling and are able to pass your knowledge to others.
  • You are proficient in coding and you are able to deliver production ready code.
  • Your communication skills enable you to work together with many different parties throughout our organization.
  • You are not shy to ask for help of other Data Scientists in the team, and you are happy to help them out by sharing your knowledge and capabilities. You are able and willing to guide junior Data Scientists and interns in their work; you also have experience doing so in your previous roles.
  • You are a team player who strikes effective balance between independence and acting in the interest of the team.
  • You are perseverant and you do not give up when a problem is hard; you know how to deal with set-backs.
  • Your enthusiasm is contagious and inspires others to act; your act sets an example for others.
  • MSc or PhD with excellent academic results in the field of Computer Science, Mathematics, Engineering, Econometrics or similar.
  • At least 6 years work related experience in a similar role and/or environment, including:
  • Machine Learning: Classification, Regression, Clustering, Unsupervised methods, Text Mining. You have an excellent understanding of Random Forests, Gradient Boosting, Neural Networks, Logistic Regression, SVM, KNN, K-Means, etc. Parametric and non-parametric statistics is a pre.
  • Programming Languages: Python and R. Scala is a pre.
  • Tools: Spark, Hadoop.
  • Database handling: SQL, Hive. Familiarity with Oracle, Netezza, HBase, Cassandra, Graph databases is a pre.
  • Visualisation tools: D3.js, Shiny, Angular.
Senior Data Scientist

Nice to have:

  • A background in anti-money laundering services or fraud.
  • You have extensive experience with stakeholder management from within data science projects.
  • Your enthusiasm is visible and you are good with mobilizing people for our data driven purpose.
  • You like working in cross-functional teams to realize an ambitious goal.
  • Experience with working in an agile/scrum way, but at least you should have a strong willingness to do so.
  • You have extensive experience with transforming data to added value for your stakeholders. You are able to see things from a different perspective and to make original solutions work in practice; when suitable you propose such endeavors to stakeholders.
  • You are able to see where ING can set further steps towards becoming a truly data driven bank. You’re always thinking one step ahead, for example in advising about the best way of implementation.

Scope of duties

60%
  - Creating innovative scalable data driven solutions in the space of Financial Crime
 
30%
  - Work with teams to implement these solution sacross the organization
 
10%
  - Work collaboratively with an extended group of stakeholders, including but not limited to Operations, Compliance, Engineering, Legal,Corporate Audit
 

Uprzejmie informujemy, iż skontaktujemy się z wybranymi kandydatami.

Jeżeli w przyszłości, chciałbyś/chciałabyś brać udział w innych rekrutacjach prowadzonych przez ING Business Shared Services B.V. sp. z o.o. Oddział w Polsce z siedzibą w Katowicach, potrzebujemy Twojej dodatkowej zgody:  „Wyrażam zgodę na przetwarzanie moich danych osobowych na potrzeby przeprowadzenia przyszłych rekrutacji.”

W przypadku wyrażenia zgody na przetwarzanie Twoich danych osobowych na potrzeby przyszłych rekrutacji informujemy, że będą one wykorzystywane przez okres 2 lat. Wszystkie informacje dotyczące przetwarzania Twoich danych osobowych znajdziesz tutaj.

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