Data Science Chapter Lead - Hands-On & Strategy

ING Hubs Türkiye

Fatih

Hybrid

TRY 600,000 - 1,000,000

Full time

14 days+

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Benefits offered by this job

Welcome Leave: 14 days

Career opportunities across borders

Personal growth and development

Dynamic, collaborative culture

PACE methodology culture

Global exposure to international teams

English language development support

Remote work opportunities throughout:

Job summary

ING Hubs Türkiye is seeking a Chapter Lead for Advanced Analytics to blend people leadership with hands-on data science delivery. You will build and guide a high-performing chapter, allocate capacity for global priorities, and mentor team members to grow craft and expertise, while delivering on complex analytics initiatives across pricing, risk and customer insights.

You will lead by example in an agile, collaborative, multi-disciplinary setting, fostering continuous improvement and delivering

Qualifications

Bachelor's degree in mathematics, engineering, computer science or econometrics.
Proven management experience in an Agile organization; matrix setup a plus.
Strong analytic skills.
Experience as a data scientist in retail domain.
Knowledge of the tribe's business domain.
Track record in analytics, backlog management and resource planning.
Ability to lead experts in a complex, dynamic environment and empower teams.
Passion for developing teams to craftmanship and growth.
Mindset focused on continuous improvement.
Excellent Python and Spark skills.
Excellent English.
Agile/Scrum experience.

Responsibilities

Develop a view on the future of the DS capability and drive ongoing development of your chapter.
Collaborate with other Chapter Leads to align capabilities and capacity for delivery.
Allocate chapter capacity for global backlog and priorities.
Steer and develop chapter members to meet career and organizational goals.
Contribute hands-on data scientist work on projects.
Manage retail DS projects in lending, personalization and pricing.
Advise on craftmanship development needs for Data Science.
Manage performance and set objectives for team members.
Collaborate on global backlog deliveries.
Attract and retain top talents, leading interviews when needed.