How you’ll help us achieve it Wave is now the largest financial institution in Senegal, with over 7 million users. And, we’re still in the early days of our product roadmap and potential impact on people’s everyday lives. We are looking for an experienced Data Analyst to join our People Tech team. In this role, you’ll; Be embedded in the HR Tech team where you will work closely with senior People Leads, the wider People Ops teams and operational teams. Navigate large data sets to identify drivers that can improve People outcomes and generate testable hypotheses. Design, develop, implement and analyze experiments related to product features and operational processes. Take full ownership of the analytics process - from project scoping and design through communicating findings to stakeholders. Derive insights from People data, visualize and communicate these in ways that improve user and business outcomes. Analyze and mine data for trends and patterns with a focus on diversity, turnover, retention, talent acquisition, reward, and other areas of the business as required. Identify and communicate data issues/concerns to maximise data quality and improve insight. Help find, test and implement process improvements to make our operations more efficient. Ensure high standards of data privacy, accuracy, and quality are maintained. Oversee dashboard and data warehouse functionality, working closely with People Operations, IT, and data engineering teams to ensure data quality, data governance, and system integrity. Support People Tech in day to day adhoc requests and data change requests. Key Details This is a fully remote role. Candidates must be based in one of our talent hub countries (UK, Spain, USA, Canada, Kenya and Ghana) or in one of our operating markets in Africa including Senegal, Côte d'Ivoire, or Burkina Faso. Wave covers travel once per year to one of our operating countries in Africa, as well as a yearly stipend of $1,200 to meet with coworkers. Our salaries are competitive and are calculated using a transparent formula, paid in your local currency equivalent), plus a generous equity package. Major benefits: Subsidized health insurance for you and your dependents and retirement contributions (both vary from country to country). 6 months of fully paid parental leave and subsidized fertility assistance. Flexible vacation, with most folks taking between 30-40 days per year. $10,000 annual charitable donation matching. Requirements Education and Experience 5 years experience as a product analyst, data analyst, data scientist or similar role. Experience working in large operational settings (example: support/call centers, product management, fleet management, supply chain operations, retail operations etc). Fluency in English. French is a plus. Technical skills Proficiency in statistical analysis, data cleaning and preparation and data manipulation in Python. Advanced SQL skills (experience with dbt is required). While data architecture is not a strong requirement, having experience in it will be helpful in this role. Proven expertise in discovery, hypothesis testing and inference over fuzzy problems and large data sets. Strong hands-on experience with visualization platforms (e.g. Tableau, PowerBI, Looker). Excellent communication skills. You’ll be working closely with operations leads so being able to communicate insights to non-technical stakeholders is a key skill we are looking for. You might be a good fit if you Have worked on a cross functional product team. Are able to work fairly independently. This role is a senior role in an emerging team at Wave. An expectation is that you’ll be able to lead and run with a problem (with support of the broader team). Can communicate clearly with your colleagues in different roles (HR Leads, engineers, data scientists, operations leads, senior management). Have run a bunch of experiments and know what to do when things do not go as planned. Excel at choosing the right complexity of analysis for any given business problem, from simple SQL queries to complex experimentation. Have experience mentoring, training or coaching more junior analysts. LI-MM1 LI-REMOTE