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    Automation Lead for Wholesale Bank Credit Risk Modelling Data - Warsaw, Polska - ING

    ING
    ING background
    W pełnym wymiarze godzin
    Opis

    We are looking for you, if you are:

  • product oriented leader and person who gets energized by creating business value and delivery,
  • an inspiring people manager with at least 2 years' experience, who like to work with end to end responsibility for both product delivery and team building and long-term development,
  • a leader with high agency and focus on getting thigs done,
  • a data professional with at least 3 years of working experience with data solutions like data warehousing, data lakes, data marts, reporting, preferably within risk domain,
  • person who worked previously within banking or finance industry,
  • a pro-active sparring partner/advisor to Senior Management,
  • a naturally collaborative person who listens and invests in others to achieve common,
  • fluent in English and have very good communication skills,
  • willing to work in an international and inclusive team focused on creativity and modernity,
  • organized & persuasive attitude; you like to interact and build relationships and are a role model in these aspects.
  • You'll get extra points for:

  • quantitative background, . a MSc or PhD degree in . (Financial) Econometrics, Financial Mathematics, Quantitative Financial Economics, Mathematics, Statistics, Physics,
  • experience with data solutions like data warehousing, data lakes, data marts, reporting, preferably within risk domain,
  • experience with ML or statistical modelling,
  • in depth credit risk domain knowledge, including regulatory models (IRB, IFRS9),
  • having a keen eye on innovation,
  • strong analytical and problem-solving capabilities,
  • experience with the agile way of working.
  • Your responsibilities:

  • manage squad leads and people in the squads (data developers, data analysts, business analysts, statistical programmers, report developers, data scientists) (depending on squad), organized in 2-3 teams within your product team,
  • setting vision & goals for Wholesale Bank Credit Risk Modelling Data Automation product like:designing and implementing strategic flows via data marts, data lakes and data products,automating data disclosure for modelers and validators,increasing efficiency of data delivery processes,
  • ensure quality of service provided by your product within Risk Hub Data, Tools and Reporting area by being part of Risk Hub team within ING Hubs,
  • manage squad leads and / or other product leads located in other global locations of ING,
  • cooperating with main local and international senior stakeholders,
  • actively supports and searches for new business opportunities to grow area and Tribe,
  • continuously focuses on creating the optimal lay out for the product ream considering strategic priorities, customer needs, target architecture etc.,
  • ensure continuous improvements, promote a feedback culture and drive team happiness in alignment with tribe and domain lead vision and strategy,
  • accelerate and strategically organize the recruiting and the onboarding of new talents.
  • Information about the squad:

    The Risk Hub Data, Tools & Reporting department is and international team of over 150 professionals. Our expertise lies in data analytic, building solutions for structural data flows and reporting alongside building tools for model development. Our team handles data for modeling activities throughout ING, working closely together on international projects with the teams in Amsterdam and other locations.

    Delivered data, tools and reports are core to the success of ING and include data for IRB and IFRS9 models (PD, LGD, EAD) for retail and wholesale portfolios, as well as non-regulatory models, multiple reports within CRO domains, tools that automate and streamline model monitoring and model development.

    We invite you to join for leaderships positions within our team.

    The role naming convention in the global ING job architecture will be "Lead Financial Risk II".



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