Data Scientist

Remotive

Remoto

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2 horas atrás

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Nenhuma candidatura

Sobre

About Us

At Félix, we're building the financial ecosystem for Latin immigrants in the U.S., starting with a revolution in remittances. Our core product is an AI-powered chatbot built on WhatsApp, allowing our users to send money home as easily as sending a text message. We leverage cutting-edge technology like AI, blockchain, and stablecoins to make cross-border payments faster, more affordable, and more accessible than ever before.

We are a hyper-growth Series B company, backed by over $100 million in funding from top-tier global investors, including QED, Castle Island, Switch Ventures, HTwenty, Monashees, and General Catalyst Customer Value Fund. This isn't just about the numbers; it's a testament to the trust our investors have in our vision and our team. Additionally, Félix was selected as an “Endeavour Entrepreneur” and was a recipient of the CrossTech Fintech Startups Award. We are a group of extremely talented and dedicated high-performers, united by our shared obsession with a single goal: empowering our customers. We are all owners of Félix, driven by a bias for action and a true experimentation spirit to get shit done with urgency and focus.

Joining Félix means you will be part of a team building a legacy, a company that will outlive us all. This is a rare opportunity to apply your skills to a deeply meaningful mission—serving a community that has been underserved for too long. We are a team that is fiercely loyal to each other, where radical transparency and constructive feedback are how we grow and push for excellence. We are bold, we care less about what others are doing, and more about creating sustainable value and a product that truly makes our users' lives better. We are building the future, today.

About the Role

As a Data Scientist for our Fraud team, you will be on the front lines of protecting our company and our customers. You will leverage your expertise in machine learning, statistics, and data analysis to design, build, and deploy sophisticated models that detect and prevent fraudulent activity in real-time. This is a high-impact role where you will see your work directly translate into protecting millions of dollars and ensuring a trustworthy platform for our users.

Responsibilities

End-to-End Model Development: Own the entire lifecycle of fraud detection models, from data exploration and feature engineering to model training, validation, deployment, and monitoring.
Advanced Analysis: Conduct deep-dive investigations into emerging fraud patterns and user behavior, using clustering, outlier detection, and other unsupervised techniques to uncover hidden risks.
Experimentation: Design and execute A/B tests to measure the impact of new models, rules, and strategies on both fraud detection rates and user experience.
Stakeholder Collaboration: Partner closely with Product, Engineering, and Operations teams to translate business needs into data science solutions and communicate complex results to non-technical audiences.
Productionalize Models: Deploy, monitor, and maintain machine learning models in a cloud environment, ensuring high availability and performance.
Reporting & Visualization: Build and maintain dashboards using tools like Tableau or Looker to track key performance indicators (KPIs) like fraud loss rates, false positive rates, and model performance

Requirements

Must-Haves:

Experience: 3-5 years of experience in a hands-on data science role, building and deploying machine learning models.
Python: Expert-level Python for data analysis and modeling (pandas, scikit-learn, etc.).
SQL: Advanced SQL skills for complex data extraction and manipulation.
Machine Learning Modeling: Deep experience with tree-based ML models (XGBoost, CatBoost, LightGBM) and statistical models (Logistic Regression, Lasso/Ridge).
Sampling Techniques: Strong understanding of sampling techniques for handling highly imbalanced datasets.
Unsupervised Learning: Practical experience with clustering and outlier detection techniques (e.g., K-Means, K Nearest Neighbors, Isolation Forest).
Model Lifecycle & Cloud: Proven experience with the full modeling lifecycle, including model deployment, monitoring, and maintenance on a cloud platform like GCP, AWS, or Azure.
Communication: Excellent stakeholder management and communication skills, with a demonstrated ability to explain complex technical concepts to diverse audiences.
Analytical Rigor: A solid foundation in statistics and experience designing and analyzing A/B tests.
Communication: Advanced English level

Nice to have

Domain Experience: Direct experience in a FinTech, payments, or risk/fraud-focused role.
MLOps: Hands-on MLOps experience (e.g., CI/CD for models, versioning, automated retraining).
Model Explainability: Knowledge of model explainability frameworks like SHAP or LIME.
GCP / Vertex AI: Experience with Google Cloud Platform (GCP), especially Vertex AI.

These are the applicable requisites, although equivalent competencies in any of the above will also be considered.

What We Offer

Competitive salary
Initial stock options grant
Annual performance bonus
Health, dental, and vision plans
Remote work environment, although we have offices in Miami and México City and would love to work in hybrid model if you are up to it.
Continuous learning opportunities
Unlimited PTO
Paid parental leave
Empowering opportunities for growth in a dynamic entrepreneurial environment

Equal Opportunity Employer

At Félix, we are committed to providing equal employment opportunities to all qualified employees and applicants without regard to race, religion, nationality, sex, sexual orientation, gender identity, age, or disability. This policy applies to all terms and conditions of employment, including recruitment, hiring, placement, promotion, training, compensation, benefits, and termination.

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