Data Scientist - Analytics

ING Group

Bucharest, Romania

As a Data Scientist, your mission is to analyze complex datasets, uncover patterns, and develop advanced analytical solutions that improve products, services, and decision-making across Retail Banking.

About the team

You’ll join a highly analytical team within Retail Banking, focused on turning complex data into clear, actionable insights.

The team works in a collaborative, data-driven environment, partnering closely with Product, Marketing, Operations, and other stakeholders to deliver scalable, production-ready analytics solutions.

Your day‑to‑day

As a Data Scientist working in an Agile environment, you will contribute to the squad’s purpose by owning data science problems end-to-end, from business understanding to deployment and governance.

In this role, you will:

Analyse large, complex datasets to identify patterns, trends, and insights that support business strategy and decision-making;
Translate business questions into data science problems, defining data requirements, analytical approaches, and implementation plans;
Develop and apply advanced analytics, including statistical analysis, machine learning models, and predictive techniques;
Build, test, and deploy data products and machine learning models at scale on data platforms;
Perform data exploration, cleaning, transformation, and feature engineering to ensure high-quality analytical outputs;
Deliver clear insights, visualisations, and storytelling to technical and non-technical stakeholders, enabling a data-driven culture;
Collaborate with cross-functional teams (Product, Marketing, Operations) to align analytics solutions with business goals;
Ensure proper model governance, including documentation, validation, monitoring, and compliance with internal standards;
Contribute to building reusable datasets, pipelines, and scalable analytical components;
Apply best practices in data privacy, security, and ethical use of data and AI models;
Identify opportunities for automation and optimization of analytical processes;
Provide guidance and share knowledge within the team to support capability building and continuous improvement.

What you bring to the team

Education & Experience: Master’s degree in a quantitative field (Mathematics, Statistics, Economics, Finance, Computer Science) and 3–6+ years of experience in data science, analytics with ability to work independently on complex topics;
Advanced Analytics & Technical Skills:
- Strong knowledge of statistical analysis, data exploration, and machine learning techniques;
- Strong experience with programming languages such as Python (and PySpark);
- Ability to work with large datasets and apply robust analytical processes (data cleaning, modelling, forecasting, pattern recognition);
- Familiarity with data visualization tools to communicate insights effectively.
Ownership & Collaboration: Ability to independently frame complex business problems, work in cross‑functional Agile squads, and take ownership from problem definition to production and governance;
Communication & Storytelling: Strong communication skills, capable of explaining complex analytical trade‑offs to both technical and non‑technical audiences.