Senior Data Scientist (Finance, Stockholm/Helsinki)

Job summary

This role involves leveraging data and analytics to enhance the banking experience for Private Banking customers in the Nordic region. The position focuses on providing insights, driving automation through model-based solutions, and optimizing processes to ensure effective customer interactions across various channels.

Qualifications

• 4-5 years of experience in data analytics or data science.
• Proven expertise in advanced statistical modeling and machine learning techniques in a production setting.
• Strong analytical skills with hands-on experience in Python or R, SQL, and modern data platforms.
• Familiarity with cloud-based data and analytics environments such as Azure, AWS, or GCP.
• Experience in developing dashboards or insights using BI tools like PowerBI or Adobe Analytics.
• Background in designing Data Science experiments and managing the model lifecycle.
• Proficient in using analytics platforms like Databricks or Snowflake.
• Experience with DevOps tools, including version control systems and CI/CD pipelines.
• Ideally, experience in Agile or SAFe environments.

Responsibilities

• Develop data-driven insights and segmentation frameworks to enhance customer experiences.
• Identify opportunities for performance improvement in digital sales and engagement through data exploration.
• Collaborate with cross-functional teams to align analytical solutions with business needs.
• Contribute to A/B testing, uplift modeling, and performance evaluation using statistical methods.
• Partner with marketing automation and digital marketing teams to deploy and monitor analytical models.
• Share insights and best practices with colleagues across different regions and business units.
• Act as a liaison between data science and business objectives to ensure alignment of analytical solutions.

Skills

• Strong analytical mindset with a focus on translating complex data into business value.
• Excellent communication skills for conveying technical concepts to non-technical stakeholders.
• Ability to thrive in a dynamic environment and drive results through data-driven decision-making.

Education

• Relevant degree in Data Science, Statistics, Mathematics, or a related field is preferred.

Tools

• Proficiency in Python or R, SQL, BI tools (PowerBI, Adobe Analytics), and cloud platforms (Azure, AWS, GCP). Experience with analytics platforms like Databricks and Snowflake, as well as DevOps tools for production implementation.