The Role
The Data Scientist will develop and implement ML models, analyze financial data, create dashboards, and collaborate with various teams to enhance decision-making processes for underserved communities.
Summary Generated by Built In
About Nclusion
About the Role
What You’ll Do
Nclusion is on a mission to provide traditional financial services to 1.5 billion people worldwide without access today. Without a secure way to save, invest, or transfer money, individuals are not empowered to accumulate short or long-term wealth. We're changing that by bridging the gap between traditional banking and the communities that need it most.
As a Data Scientist at Nclusion, you will be responsible for developing and implementing machine learning and data models to analyze financial and user data, create comprehensive reports and visualizations, and improve our decision-making processes for underserved communities. You will also build and maintain data dashboards to track key metrics and provide actionable insights to stakeholders.
- Build ML Models – Develop models for credit risk assessment, fraud detection, and customer segmentation
- Data Analysis – Extract meaningful insights from complex financial datasets, create robust feature sets, and develop innovative approaches to evaluate creditworthiness
- Risk Assessment Systems – Design and implement automated risk scoring systems
- Fraud Detection – Create and maintain ML models to identify potential fraud patterns
- Model Monitoring and Optimization – Continuously monitor model performance, identify bias, and optimize algorithms
- Cross-functional Collaboration – Work closely with engineering, product, finance, and compliance teams to implement ML solutions that meet regulatory requirements and business need
- Data Visualization & Reporting – Design and maintain comprehensive dashboards and reports to communicate key insights to stakeholders
- 8+ years of experience working with machine learning, data science, and analytics in production environments
- Extensive experience with Python libraries for data analysis and deep learning frameworks
- Proven track record implementing supervised and unsupervised learning algorithms and deep learning models
- Strong foundation in statistical analysis, experimental design, and data visualization
- Experience with big data processing frameworks and databases (BigQuery, Airflow, Spark, PosgreSQL)
- Understanding of financial services, credit risk assessment, and fraud detection
- Ability to explain complex technical concepts to non-technical stakeholders and collaborate effectively across teams
- A Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field (or equivalent practical experience)
Benefits and Perks
- 📈 401k with 4% match
- 🩺 Medical Insurance
- 🦷 Dental Insurance
- 👓 Vision Insurance
- 💸 Competitive compensation & equity – We believe in sharing success.
- ✈️ Flexible PTO – We focus on impact, not tracking vacation days. We encourage a minimum of 14 days.
- 🍽️ In-office lunch, team events & culture
Yearly Salary: $150,000 - $260,000
In our commitment to fostering a diverse and inclusive workplace, we value the unique perspectives and experiences each individual brings to our team. We encourage all candidates, regardless of background, to apply. Your skills, talents, and potential contributions matter deeply to us, and we believe in creating an environment where everyone has an opportunity to thrive. We recognize that meeting every listed requirement may not always be possible, but we value passion, determination, and a willingness to learn. Your application is an opportunity for us to discover the exceptional qualities you bring.
Top Skills
Airflow
BigQuery
Postgres
Python
Spark
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The Company
What We Do
Nclusion is a financial technology company dedicated to empowering underserved and unbanked populations in the developing world. By providing accessible, affordable, and inclusive financial services, we’re on a mission to drive financial inclusion and promote economic growth and entrepreneurship.
