Data Scientist

About Addi

We are a technology company working to transform credit and banking in Latin America starting with point of sale finance. We aim to build fair, simple and affordable financial services that empower our clients, treating them with dignity, and building financial freedom. We launched in February 2019 and have already served millions of clients and disbursed millions of dollars.

We operate as a full stack startup. We have built our core systems and processes from scratch, and we believe our technology and analytics platform will drive our progress into the years to come. We come at this with deep experience building and growing technology teams and financial products. As important as what we do is how we do it. We are a conscious company and are deeply committed to working and living our five core values - A company of owners inspiring colleagues, we pull rabbits out of hats, we care and we trust, act with integrity, win today every day, and scale exponentially.

We are backed by Andreessen Horowitz, Monashees, Village Global, and an outstanding team of individual angels, including Kevin Ryan, Josh Abramowitz, and Scott Weiss.

Mission

Design, implement, and monitor scalable ML models to better understand customer behavior and needs, enabling data-driven strategies that enhance engagement, growth and retention. Collaborate with cross-functional teams to transform insights into actionable solutions that drive Addi’s growth and enhance customer experiences.

What you will do

• Develop and Implement ML Models: Design, implement, and scale machine learning and ML models to analyze customer behavior, optimize marketing strategies, and improve overall engagement with Addi’s platform. This includes leveraging techniques like supervised and unsupervised learning, propensity scoring, and recommendation systems.

• Manage Data Pipelines and Model Deployment: Collaborate with data engineering teams to design and optimize data pipelines that support the seamless deployment of the models into production. Ensure that models are integrated efficiently and can be scaled, maintained, and monitored for performance in a live environment.

• Monitor and Evaluate Model Performance: Continuously monitor the performance of deployed models, evaluate their impact on business metrics, and iterate to improve their accuracy, scalability, and overall performance.

• Collaboration and Knowledge Sharing: Work closely with product managers, marketing teams, and stakeholders to translate data insights into actionable strategies, and actively participate in cross-functional meetings to align ML models with business goals.

• Innovate and Improve Processes: Continuously innovate by proposing ML models, algorithms, or tools that enhance customer experience, optimize product recommendations, and improve overall marketplace performance.

• Conduct A/B Testing: Design and execute A/B tests to assess the impact of different offers, product recommendations, and marketing strategies on customer engagement and conversion rates. Analyze the results to understand customer sensitivity to various factors and refine approaches accordingly.

Requirements

• Technical expertise:

  • 3+ years of experience in data science areas focused on client segmentation, marketing optimization, and recommendation systems, including end-to-end model design from scratch, development, deployment, and scaling.

  • Strong knowledge of statistics and mathematics.

• Programming languages and tools Proficiency:

  • Proficiency in data management with SQL

  • Machine learning modeling: Python

  • Experience with python libraries such as TensorFlow/Keras/Scikit-learn/ PyTorch

• Advanced expertise in machine learning algorithms:

  • Deep knowledge in classification models, particularly for propensity scoring: Proficiency in developing and applying propensity score models to predict customer behavior, such as the likelihood of purchasing a product, or engaging with a specific channel.

  • Experience in model interpretability: The ability to explain model results using SHAP, LIME, and other explainability techniques to ensure transparency and stakeholder trust.

  • Recommendation algorithms: Familiarity with collaborative filtering, content-based filtering, and hybrid models for product recommendations or LLMs applied to this field.

  • Proficiency in statistical methods:

    • Proven experience in A/B testing and experimental design: Designing, executing, and analyzing experiments to validate the impact of models and business strategies.

• Values and Ownership:

  • Strong communication skills: Ability to clearly explain complex technical concepts and model results to non-technical stakeholders and senior leadership, influencing key business decisions.

  • Proactive Problem Solver: Demonstrates ownership by anticipating challenges, identifying opportunities for improvement, and taking initiative to drive solutions.

  • Customer-Centric Mindset: Prioritizes understanding customer behavior and needs to design solutions that enhance engagement and satisfaction.

  • Accountability for Results: Takes responsibility for the success of projects, ensuring models and solutions meet both technical and business expectations.

  • Ethical Responsibility: Upholds high standards of data privacy and ethical modeling practices.

• Desirable Qualifications

  • Bachelor's degree in: Physics, mathematics, statistics, economics, or computer science.

  • Experience with marketplace platforms

  • Experience in data science roles at start-ups

Benefits

• Work on a problem that matters and help change customers’ lives.

• Build a lasting company from the very beginning, helping define every aspect of it.

• Massive market opportunity ahead of us; we are growing faster than pretty much any other fintech lender was at our stage.

• Work alongside a great and diverse team that cares about what we are doing and how we are doing it.

• Generous compensation, including equity, 100% health insurance (and 1000% for dependents), flexible time-off, learning budget, and visa sponsorship for foreigners.

How the hiring process looks like

• Meet with our recruiter for a 30-minute video chat. We will get to know you better, understand what you’re looking for, and answer any questions you might have about ADDI.

• Meet with our Data Science Lead for a 60-minute video chat interview. Here, we will ask you questions about your technical background and basic computer science concepts. You will be able to ask any questions about the culture and how we work at ADDI.

• Complete a simple take-home challenge within a 1-week window. With this technical challenge, we want to see your technical expertise solving a real-world problem. We expect that you invest 5 hours or less in developing a working solution.

• Meet with a Data Scientists and the Data Science Lead for a 60-minute chat to talk about your take-home exercise submission and any questions you might have.

• Meet onsite with one of our founders for a 30-minute chat to talk about the vision of the company, what we are building and how you will contribute to our product.