Data Analyst

Requirements

• Proven experience in designing and analyzing A/B tests and other experimental designs.
• Strong proficiency in statistical analysis and data visualization tools (e.g., R, Python, SQL, Tableau).
• Excellent analytical and problem-solving skills.
• Ability to communicate complex data insights in a clear and actionable manner.
• Experience with web analytics tools (e.g., Go

Benefits

Additional Information

About ING Hubs Following ING's strategic ambition to deliver a superior experience to its customers worldwide, the hubs network contributes to fostering efficiency and digitalization across ING. Providing concentrated expertise along with scalable and sustainable solutions, the hubs focus on straight-through processing, delivering automated services like software development, data management and retail operations. 𝑃𝑟𝑒𝑠𝑒𝑛𝑡 𝑖𝑛 𝑃𝑜𝑙𝑎𝑛𝑑, 𝑅𝑜𝑚𝑎𝑛𝑖𝑎, 𝑆𝑙𝑜𝑣𝑎𝑘𝑖𝑎, 𝑡ℎ𝑒 𝑃ℎ𝑖𝑙𝑖𝑝𝑝𝑖𝑛𝑒𝑠 𝑎𝑛𝑑 𝑇𝑢𝑟𝑘𝑖𝑦𝑒, 𝐼𝑁𝐺 𝐻𝑢𝑏𝑠 𝑒𝑚𝑝𝑙𝑜𝑦 𝑚𝑜𝑟𝑒 𝑡ℎ𝑎𝑛 11,000 𝑝𝑟𝑜𝑓𝑒𝑠𝑠𝑖𝑜𝑛𝑎𝑙𝑠 𝑖𝑛 𝑑𝑜𝑚𝑎𝑖𝑛𝑠 𝑠𝑢𝑐ℎ 𝑎𝑠 𝑠𝑜𝑓𝑡𝑤𝑎𝑟𝑒 𝑑𝑒𝑣𝑒𝑙𝑜𝑝𝑚𝑒𝑛𝑡, 𝑑𝑎𝑡𝑎 𝑚𝑎𝑛𝑎𝑔𝑒𝑚𝑒𝑛𝑡, 𝑜𝑝𝑒𝑟𝑎𝑡𝑖𝑜𝑛𝑠 𝑜𝑟 𝑛𝑜𝑛-𝑓𝑖𝑛𝑎𝑛𝑐𝑖𝑎𝑙 𝑟𝑖𝑠𝑘. ING Hubs Turkiye core capabilities, 𝐑𝐞𝐭𝐚𝐢𝐥 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐚𝐧𝐝 𝐓𝐞𝐜𝐡, have us looking for data experts, developers and other professionals to get onboard in our Istanbul office located in Technopark, Vadistanbul. 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫 𝐈𝐍𝐆 𝐇𝐮𝐛𝐬 𝐓𝐮̈𝐫𝐤𝐢𝐲𝐞 ING Hubs Turkiye is looking for talents to join an international network of professionals. Building on an existing framework and shared mission, our up-and-coming team will bring its unique personality and skills set to provide borderless services with bank-wide capabilities. We value strong work ethics, knowledge sharing and flexibility in our way of working - it is both our promise to you and what we look for in new colleagues. Let's meet! ING Analytics ING Analytics is a new unit responsible for realizing this vision for ING, differentiating ING as a leader in data-driven organization, within the banking sector and beyond. The team consists of a number of Global Analytics Centre of Excellences around the bank's key capabilities (such as Pricing, Risk Management, Financial Crime, Customer Intelligence and People Analytics.) as well as strong coordination areas around data management, technology, customer journey, UX, as well as external partnerships. The team and Topics: HyPe, short for HypePersonalisation is one of the key Generative AI focus areas where ING is implementing solutions in. HyPe is centered around delivering a superior customer experience by being highly personal and relevant with our customers via every interaction we have with them. This includes ads our potential future customers might see on our social media channels, or messages our existing customers might get via their app or email. Our vision is to leverage on GenAI to create highly relevant content for every type of customer group, in different formats, languages, channels, and do this at scale in an instantaneous manner. As we start this journey, experimentation is key to find the right balance and quality of the generate content. We work with ING markets Europe and we are looking for a Data Analyst specializing in experimentation to support us in this exciting topic! Generic Tasks: Design, implement, and analyze A/B tests and other experimental designs to evaluate the impact of GenAI based marketing campaigns Collaborate with cross-functional teams, including product managers, engineers, and marketers, to develop and execute testing strategies. Develop hypotheses and create detailed test plans, including defining key metrics and success criteria. Analyze test results using statistical methods to derive actionable insights and make data-driven recommendations. Present findings and recommendations to stakeholders in a clear and concise manner. Monitor ongoing tests to ensure data quality and integrity. Continuously improve experimentation processes and methodologies. Stay up-to-date with industry trends and best practices in experimentation and data analysis. GenAI Project Specifics: Audience Segmentation: Identify the right data dimensions and analytical models to proxy customer behaviours and needs, enabling the creation of distinct customer segments for more targeted and effective campaigns. Collaboration on Audience Development: Work with product teams to define and refine customer sub-audiences, ensuring they are unique and aligned with campaign goals for improved targeting. Feedback and Insights Gathering: Collect and synthesize feedback on campaign performance, translating it into actionable insights for the Retail Analytics team to refine future campaigns and personalization strategies. Performance Monitoring & Reporting: Track and report on campaign results, especially A/B testing outcomes, and provide recommendations for ongoing optimization of HyPe Engine output quality and features

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