Founded in 2018, Gozem is today a technological group of more than 400 people, agile and ambitious, which offers via its mobile application a very wide range of services including transport, delivery, financing, mobile money and many others, to African users. Present in Benin, Togo, Gabon and Cameroon, our group's ambition is to become "Africa's Super App" by establishing itself throughout French speaking Africa. Our solution is 100% focused on the African market, serving drivers, customers, traders and soon, SMEs in our areas of activity.We are a multinational group, with a strong presence in several cities and pride ourselves on helping to improve the lives of local communities through the digitalisation of the market and the introduction of technology-based efficiencies.Are you looking to grow in a challenging and friendly environment? Do you want to evolve and progress in dynamic and disruptive digital contexts?Join us in building a new African digital ecosystem that improves the quality of life. Together, let's make Africa smile!Website:Google Play Store:Apple App Store:Glassdoor:What is a Senior Data Scientist at Gozem?At Gozem, our Senior Data Scientist is a strategic role at the intersection of data science, applied machine learning, and fintech innovation. In the Gozem Money business, you will design and implement advanced models to analyze transactional and behavioral data, predict outcomes, detect risks, and unlock new growth opportunities.This role goes beyond model-building: you will take ownership of the end-to-end data science workflow, including fetching and cleaning data from diverse sources, building scalable models, and deploying them in production. You will collaborate closely with business leaders, engineers, and product managers to translate complex datasets into actionable insights that shape financial inclusion in Sub-Saharan Africa.As a senior member of the data team, you will also mentor junior team members, contribute to our data culture, and play a key role in ensuring insights quality, governance, and reliability across our pipelines.Your tasks:
Build and deploy advanced statistical, machine learning, and AI models for use cases such as fraud detection, credit scoring, customer segmentation, churn prediction, and personalization.
Design and implement analytics pipelines: clean, structure, and consume raw data from our data lakehouse, and other sources.
Lead data-driven decision-making: collect, transform, analyze, and communicate insights that directly inform product, risk, and growth strategies.
Manage and deliver data science projects from conception to production, ensuring alignment with business objectives.
Collaborate with cross-functional teams (Product, Engineering, Operations, Finance) to translate business problems into data solutions.
Monitor and optimize the performance of models and pipelines, ensuring the related solutions remain reliable, fair, and scalable.
Mentor junior data scientists and analysts, providing guidance on best practices and methodologies.
Stay up-to-date with the latest advances in AI/ML, MLOps, and fintech analytics, and help integrate them into Gozem's stack.
You are the right person for this job if you ...
Have strong expertise in machine learning, statistical analysis, and predictive modeling, and know how to bring models from prototype to production.
Have hands-on experience with transactional data, financial services data, or digital payments.
Are comfortable with basic analytics engineering tasks: writing efficient SQL queries, cleaning large messy datasets, and automating data flows.
Have experience working with metadata standards, insights quality frameworks, and governance practices.
Are able to communicate complex technical concepts clearly to non-technical stakeholders and influence decision-making.
Can balance innovation with pragmatism, delivering models and insights that drive measurable business impact.
Thrive in a fast-paced environment, taking ownership of challenges and moving projects forward.
You have
Education: Bachelor's/Master's degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related field.
Experience: 5+ years of experience in data science, preferably in fintech, banking, payments, or digital platforms.
Core skills: Mastery of SQL, Python, and ML frameworks (scikit-learn, TensorFlow, PyTorch).
Analytics engineering basics: Experience with ETL & automation tools (Airflow, Dataform, or equivalent), and handling large-scale structured/unstructured datasets.
Visualization: Proficiency in Looker Studio, Metabase, or other BI tools.
Nice-to-have skills: Knowledge of R, BigQuery, GCP, or MLOps frameworks (MLflow, Kubeflow, etc.).
Tools to master: Asana, Jira, Google Suite.
Languages: French and/or English (bilingual proficiency is a strong plus).
Location: Hybrid.
What we like most
Self-motivated, autonomous, and proactive in identifying opportunities to create value with data.
A natural mentor who enjoys helping others grow.
Detail-oriented, structured, and able to manage time efficiently in a fast-paced, multi-market environment.
Excited about the challenge of using data to transform financial services in Africa.
Working conditions & benefitsWe offer our employees a fair, friendly and intercultural working environment, in which we strive to develop the talents of each individual. To achieve this, we offer:Open-space offices and teleworking time possible (to be arranged with your manager)A gross monthly remuneration defined according to our internal salary grid as well as the relevance of your past experiences for the position.An option to buy shares in GozemAn annual bonus allowing you to receive between 0 and 4.5 months of additional salary the following yearBenefits on our Super App for your travel and deliveriesA health and IT insurance packageAnd above all, the opportunity to join a young, dynamic team that has a real social impact in French-speaking Africa!Interview process
An initial introductory meeting with the recruitment manager (15 minutes)
A written interview questionnaire
A business case to be completed within 07 days
A presentation of your business case with the head of the Data team (future n+1) and a time to discuss your professional experience followed by a referral request (you give us 4 professional contacts to whom we send a questionnaire)
One final validation interview with one of our co-founders
