Data Analyst - Investments

• 3+ years of experience, ideally within the Product or Analytics field.

• 1+ years of experience in the Investments or Wealth domain

• Strong understanding of statistical methods used in the analysis of experimental and observational data (e.g. causal inference)

• Strong problem solving skills and is comfortable doing exploratory data analysis that generates insights and "so whats"

• Highly experienced with SQL and Python/R for analytics

• Experience working with one or more common data visualisation tools (Tableau, Metabase, Looker, Superset, etc)

• Good presentation skills and communication skills.

• Experience with Experimentation (e.g. AB testing, multivariate etc)

• Accelerate your career growth by joining one of Europe's most innovative banks 🚀.
• Employee benefits that range from a competitive personal development budget, work from home budget, discounts to fitness & wellness memberships, language apps and public transportation.
• As an N26 employee you will have access to a Premium subscription on your personal N26 bank account. As well as subscriptions for friends and family members.
• Vacation days vary depending on your location of work. Additional day of annual leave for each year of service.
• A high degree of autonomy and access to cutting edge technologies - all while working with a friendly team of peers of diverse nationalities, life experiences and family statuses.
• A relocation package with visa support for those who need it.

We are seeking an organised and self-motivated Data Analyst to work embedded in our Investments team, to help shape the development of one of the world's leading FinTech products.

As a Data Analyst, you will enable our product and business segments in the Financial Empowerment domain, specifically Investments, to make data-driven decisions. You will monitor, measure and analyse the effectiveness of your product teams' initiatives, helping to drive the strategy of your business segment. You will apply robust analytical approaches, including experimentation and causal inference methods where appropriate, to understand the impact of product and business decisions on customer and business outcomes. You are here to establish a data mindset and thereby foster a culture of continuous learning and improvement. You will work in a cross-functional setup, collaborating closely with other analysts, engineers, designers, and product managers.

• Help us set the right goals: Develop clear and measurable targets based on an initiatives' scope. Improve our overall forecasting and goal setting capabilities.

• Handle stakeholders: Be an internal go-to-person for your teams when it comes to data related questions.

• Evaluate initiatives: Support product experimentation and impact measurement initiatives; design experiments and causal inference analyses, obtain cross-functional alignment, execute robust analyses, and deliver actionable insights. Share these learnings through clear documentation and concise, empathic communication.

• Contribute to self-serve data platform: Help building the right analytics foundations,by pairing up with technical peers, so our product teams can interact with data and extract the right insights themselves.

• Provide monitoring tools: Build the dashboards your team looks at every week to make sure they are impacting our company OKRs.

• Improve data literacy of organisation: Educate teams to become independent when it comes to data access and understanding function led training and team wide workshops to foster data driven culture.

• Be part of our data-community: Collaborate with a broad range of analytics teams at N26 to utilise shared platforms, insights and innovations.

• Support some of the following product & business team initiatives (not limited to):

  • Support your team in discovery of new product ideas, identifying user friction points and business opportunities.

  • Evaluate your teams' continuous releases making sure they are delivering on business goals via experimental or observational methods.

  • Collaborate with UX researchers to combine qualitative and quantitative research for better product hypotheses.

  • During product development you make sure all data needed for future evaluation is being captured through set up of tracking events or as part of the backend service.

  • Drive the quantitative analysis on your segment, being responsible for the insights and business discovery on the team.