ING Bank

Financial Services

DataAnalyst

$75–115k ~AI est. Romania FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Data Analyst at ING Bank. Skills: Data analysis, Business intelligence, Data visualization. Gather large datasets. Prepare large datasets”

What You'll Achieve.

Deliver measurable business value; Enhance customer understanding; Optimize campaigns

Industry & Context.

Financial Services
Problems you'll solve

Interpret complex data; Spot trends; Generate actionable recommendations

What They're Looking For.

Must Have

University degree in Mathematics, Statistics, Economics, Marketing, Cybernetics, or a related field, Solid experience in data analysis, Proficiency with data tools such as SAS, SQL, Python, Experience creating dashboards, Experience creating campaign analyses, Experience creating product analyses, Experience with data validation

Nice to Have

Experience in banking or financial services, Experience with BI platforms (Power BI)

What You'll Do.

Gather large datasets

Prepare large datasets

Analyse large datasets

Deliver robust insights

Develop analytical datasets

Maintain analytical datasets

Collaborate with stakeholders

Collaborate with senior analysts

Identify opportunities

Design campaign analysis

Execute campaign analysis

Design product evaluations

Execute product evaluations

Coach junior analysts

Mentor junior analysts

Promote best practices

Act as main point of contact

Maintain alignment on definitions

Maintain alignment on data structures

Maintain alignment on objectives

Conduct deep-dive analyses

Identify business drivers

Enhance customer understanding

Perform quality checks

Support development of advanced analytical frameworks

Drive process optimization

Ensure reusability of scripts

Ensure reusability of methodologies

Provide support across Customer Intelligence

How You'll Work.

Team & Collaboration

Analytics peers; Pricing & Value Leads; Business stakeholders; Cross-functional projects; Data Scientists; Data Engineers

Communication Scope

Translate technical insights; Build partnerships

Process & Methodology

Agile Way of Working

Full Job Description

**Mission** At ING, we believe in giving people the freedom to grow, explore, and build what matters to them. Our Analytics capabilities stand at the heart of that mission — powering decisions that shape products, protect customers, and help millions stay a step ahead in life and business. If you’re passionate about turning data into actionable insights that drive business growth, you’ll feel right at home here. **About the team** You’ll join a **deeply analytical team** within Retail Banking, focused on turning **complex data into clear, actionable insights**. The team partners closely with business stakeholders to uncover hidden patterns, support data‑driven decision‑making, and enable leaders to maximize impact. You will work closely with Analytics peers and the Pricing & Value Leads on in‑depth and advanced analytics initiatives; the environment is collaborative, insight‑driven, and geared toward delivering measurable business value through rigorous analysis and thoughtful interpretation. **Your day-to-day** As a **Data Analyst** in an Agile Way of Working, you will be a part of a Squad and will dedicate your time and efforts to achieve the tribe/ squad’s purpose through: In this role, you will: * Gather, prepare, and analyse large datasets to deliver robust insights supporting business strategies across customer, marketing, and digital channels. * Develop and maintain dashboards, reports, and analytical datasets tailored to business needs, ensuring accuracy and clarity in all outputs. * Collaborate with stakeholders and senior analysts to identify opportunities, design and execute segmentation, campaign analysis, and product evaluations. * Coach and mentor junior analysts, promoting best practices within the team. * Act as main point of contact for cross-functional projects, maintaining alignment on definitions, data structures, and objectives. * Conduct deep-dive analyses to identify business drivers, proactively recommending actions to enhance customer unders

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