Data Analyst - Financial Crime

ING Group

Bucharest, Romania

The Mission

As a Data Analyst, you will play a crucial role in preventing financial crime by assisting with the development and implementation of advanced machine learning models used to predict fraudulent transactions. You excel in handling and analyzing highly complex data, leveraging your advanced Python skills to convert data into actionable insights, automated reports, and dashboards. Working closely with data scientists and data engineers, you will support stakeholders in making informed decisions by providing in-depth analysis and clear visualizations.

Your day to day

Even if you’ll start your day from the comfort of your home or drink your morning coffee in our office’s garden, your day will be quite similar when comes to tasks. Here are your daily responsibilities:

Identify, analyze, and interpret trends or patterns in complex data sets (both structured and unstructured textual data) in collaboration with data scientists and data engineers;
You collect relevant data, analyze and report. You clean up and process raw data, correlate different types of data, recognize patterns, and help validate Machine Learning models;
You assist with the development and implementation of the machine learning models used to prevent fraudulent transactions, being involved in activities such as exploring model improvement points, doing feasibility analyses of proposed solutions or carrying out ad-hoc analytics;
You interpret data, analyze results and deliver excellently substantiated data analyses using standard techniques and tools, which lead to improved business decisions or better data quality;
You develop automated reports and dashboards to monitor performance and track KPIs, presenting insights and outcomes in a concise and understandable manner to stakeholders;
You support tribes and squads in their decision-making by describing and visualizing discovered insights and predictions and advise your business partners with actionable insights.

What you’ll bring to the team

Experience: 2-3 years of experience within data reporting & statistics.

Tech stack/knowledge:

Advanced Python (including OOP);
SQL;
Git;
Data reporting & statistics;
Experienced in relevant BI and visualization tooling such as PowerBI, Cognos, Superset;
Ability to apply high level analytical, statistical and quantitative problem-solving skills to make actionable recommendations based on outcomes;
To take ownership on tasks assigned: you will be cultivating Analytics within the bank;
To be able to influence and convince not only peers but also the stakeholders based on analytical results;
You have integral, cross-domain knowledge and experience;
Attention to Detail: Data is precise. You make sure you are vigilant in your analysis to come to correct conclusions;
Ability to present your analysis and outcomes in a concise and understandable manner to stakeholders.