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Senior Data Scientist
FairMoney
- London, England, United Kingdom
- London, England, United Kingdom
Über
Job Summary Your mission is to develop data science-driven algorithms and applications to improve decisions in business processes like risk and debt collection, offering the best-tailored credit services to as many clients as possible.
Requirements
Strong background in Mathematics / Statistics / Econometrics / Computer Science or related field
5+ years of work experience in analytics, data mining, and predictive data modelling, preferably in the fintech domain
Strong proficiency in Python and SQL
Hands‑on experience handling large volumes of tabular data
Strong analytical skills: ability to make sense of diverse data and its application to specific business problems
Confidence working with key machine learning algorithms (GBM, XG‑Boost, Random Forest, Logistic regression)
Experience building and deploying models around credit risk, debt collection, fraud, and growth
Track record of designing, executing and interpreting A/B tests in a business environment
Strong focus on business impact and experience driving it end‑to‑end using data science applications
Strong communication skills
Passion for all things data
Tool Stack
Programming language: Python
Production: Python API deployed on Amazon EKS (Docker, Kubernetes, Flask)
ML: Scikit‑Learn, LightGBM, XGBoost, shap
ETL: Python, Apache Airflow
Cloud: AWS, GCP
Database: MySQL
DWH: BigQuery, Snowflake
BI: Tableau, Metabase, dbt
Streaming Applications: Flink, Kinesis
Role and Responsibilities
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions
Mine and analyze data from company databases and external sources to drive optimization and improvement of risk strategies, product development, marketing techniques, and other business decisions
Assess the effectiveness and accuracy of new data sources and data gathering techniques
Use predictive modelling to increase and optimize customer experiences, revenue generation, and other business outcomes
Coordinate with different functional teams to make the best use of developed data science applications
Develop processes and tools to monitor and analyze model performance and data quality
Apply advanced statistical and data mining techniques to derive patterns from the data
Own data science projects end‑to‑end and proactively drive improvements in both data and models
Benefits
Paid Time Off (25 days vacation, sick & public holidays)
Family Leave (maternity, paternity)
Training & Development budget
Paid company business trips (not mandatory)
Remote work
Recruitment Process
Screening call with Senior Recruiter
Home Test assignment
Technical interview
Interview with the team and key stakeholders
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Information Technology
Industries Non-profit Organizations and Primary and Secondary Education
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Sprachkenntnisse
- English
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