Data Scientist - Payments

at  Skillspark AB

STARTASAP

DURATION7-9 months
emagine is looking for an experienced Data Scientist to our client in Payment/Fintech domain.
Start: September/October
Duration. end of March 2025
Location: Hybrid setup from Stockholm

JOB DESCRIPTION SUMMARY:

The Global Analytics and Data Science team is seeking a Data Scientists to join us as exceptional problem solver with a passion for data insights and a relentless execution focus.
As a Data Scientist, you will spearhead our efforts to measure and enhance our payment products This role is central to our mission, offering you the opportunity to work with cutting-edge technology in a fast-paced environment. You will lead the data science projects for the initiatives that optimize transaction success rates, directly impacting our ability to offer seamless payment solutions to millions of users worldwide.

REQUIRED SKILLS AND QUALIFICATIONS:

• 5+ years of experience in analyzing multi-dimensional datasets and creating actionable business solutions.
• Strong educational background with a Bachelor’s/Master’s degree in Analytics, Engineering, Computer Science, Economics, Statistics, Mathematics, or a related quantitative discipline.
• Relevant experience and expertise on A/B Experimentation setup and measurement.
• Expertise in SQL, Excel, and visualization tools such as Looker, Tableau or Qlikview. Proficiency in a statistical programming language like R or Python is preferred.
• Demonstrable experience with big data technologies such as Teradata, Hadoop/Hive, and BigQuery.
• Knowledge of Python, Jupyter Notebooks, and SQL.
• Exceptional communication skills to effectively articulate insights and influence cross-functional teams.
• Prior experience in product analytics within a high-tech environment.

• Data Analysis and Decision Making: Utilize large, complex datasets to drive improvements in the Product. Employ advanced analytical and statistical techniques to identify trends, issues, and opportunities.
• Strategic Influence: Develop and present insights and strategic recommendations to Product and Data Science leadership. Influence product direction and strategic decisions through data-driven insights.
• Collaboration and Communication: Work closely with cross-functional teams, including product development, engineering, and marketing to implement data-driven improvements.
• Innovation and Improvement: Lead initiatives to refine existing analytical processes and develop new approaches to business challenges. Promote a culture of continuous improvement and testing.