Data Scientist (She/He/They) at Capco Singapore

, , Poland -

Full Time

Start Date

Immediate

Expiry Date

31 Mar, 26

Salary

0.0

Posted On

31 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Analysis, Python, R, SQL, Machine Learning, AI, Data Quality, Statistical Models, Predictive Models, Data Visualization, Fraud Detection, Operational Optimization, Databricks, Azure ML, SAS, Hadoop

Industry

Financial Services

Description

CAPCO POLAND Capco Poland is a global technology and management consultancy specializing in driving digital transformation across the financial services industry. We are passionate about helping our clients succeed in an ever-changing industry. We also are: Experts in banking and payments, capital markets, wealth and asset management Focused on maintaining our nimble, agile, and entrepreneurial culture Committed to growing our business and hiring the best talent to help us get there Overview: We are looking for a Data Scientist to join our Retail Banking team, focusing on Cash and Loan products in Warsaw office. This role involves bridging business needs with technology solutions, ensuring that IT systems effectively support business objectives and regulatory requirements. You will work closely with stakeholders across business and technology to deliver high-quality solutions that enhance customer experience and operational efficiency. Key Responsibilities Provide advisory services on data analysis and identify opportunities for leveraging data in the Bank’s business processes. Consult on the design of analytical and predictive models, including areas such as AML, fraud detection, and operational optimization. Advise on data quality, structure, and integration possibilities with source systems. Support in defining requirements for analytical environments and data platforms. Recommend approaches for data exploration, visualization of results, and interpretation of models. Qualifications Proficiency in analytical tools and programming languages (e.g., Python, R, SQL) and familiarity with ML/AI libraries (e.g., scikit-learn, TensorFlow). Experience in providing data analysis advisory services within the financial sector. Ability to design and evaluate statistical, predictive, and classification models to support business objectives. Strong understanding of data quality, processing, and preparation techniques for analytical purposes. Knowledge of analytical platforms and data environments (e.g., Databricks, Azure ML, SAS, Hadoop). Preferred Skills Experience in IT project consulting within banking. Understanding of regulatory frameworks impacting retail banking. Ability to recommend innovative solutions for process optimization. We offer a flexible collaboration model based on a B2B contract, with the opportunity to work on diverse projects. ONLINE RECRUITMENT PROCESS STEPS Screening call with the Recruiter Competencies interview with Capco Hiring Manager Client’s interview Feedback/Offer Joining Capco means joining an organisation that is committed to an inclusive working environment where you’re encouraged to #BeYourselfAtWork. We celebrate individuality and recognize that diversity and inclusion, in all forms, is critical to success. It’s important to us that we recruit and develop as diverse a range of talent as we can and we believe that everyone brings something different to the table – so we’d love to know what makes you different. Such differences may mean we need to make changes to our process to allow you the best possible platform to succeed, and we are happy to cater to any reasonable adjustments you may require. You will find the section to let us know of these at the bottom of your application form or you can mention it directly to your recruiter at any stage and they will be happy to help.

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Responsibilities

The Data Scientist will provide advisory services on data analysis and identify opportunities for leveraging data in the Bank’s business processes. They will consult on the design of analytical and predictive models and advise on data quality and integration possibilities.