Senior Data Scientist - BEES Fintech på AB InBev i Remote
AB InBev · Remote
Senior Data Scientist - BEES Fintech
About us
AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re
number one or two in m...
About us
AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re
number one or two in many of the world’s top beer markets, including North America, Latin America, Europe, Asia, and Africa.
About AB InBev Growth Group
Created in 2022, the Growth Group unifies our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and
Marketing teams. By bringing together global tech and commercial functions, the Growth Group allows us to fully leverage data and
drive digital transformation and organic growth for AB InBev around the world.
In addition to supporting well known global beer brands like Corona, Budweiser and Michelob Ultra, the Growth Group is home to a
robust suite of digital products including our B2B digital commerce platform BEES, on-demand delivery services Ze Delivery and
TaDa Delivery, and table top beer keg PerfectDraft.
We are an exceptional team, focused on understanding and supporting consumer and customer needs, harnessing new technology, and
scaling growth opportunities.
About BEES
BEES, our ambition is – and always will be – to put customers at the heart of everything we do. Making their lives easier and
their businesses more profitable. Through our B2B e-commerce and SaaS platform, we bring the power of digital to small and
medium-sized retailers and the companies that service them, unlocking new growth opportunities for all. With offices in São Paulo
and Campinas, we encourage our team to participate in major events and significant meetings throughout the year.
The Team: BEES is the team driving AI strategy at BEES by building end-to-end products to serve our teams, customers, and partners
across the globe. The organization is a cross-functional blend of AI/ML teams from Applied Research and Machine Learning
Engineering to Machine Learning Platform Product Management. Together, the team is responsible for building the tools and products
needed to deliver world-class AI/ML capabilities.
As a member of the BEES Fintech Data Science team, you will develop data-driven solutions for credit risk, underwriting, portfolio
optimization, pricing, and decisioning systems that operate at scale and directly impact real-time credit decisions.
What you'll do:
Be part of a high-impact fintech data science team building ABIs credit models, credit decisioning systems, and ML-powered
infrastructure that drive billions of dollars in credit transactions annually for millions of users worldwide.
Design, develop, and deploy statistical and machine learning models across the full lifecycle — from research and
experimentation to production — with a focus on credit risk, underwriting, portfolio optimization, and experimentation.
Write a substantial amount of production-grade code while conducting deep analytical and statistical research, translating
theory into practical improvements in live credit systems.
Lead and contribute to experimentation and model evaluation (offline analysis, simulations, and online tests), ensuring models
are robust, explainable, and aligned with regulatory, risk, and business constraints.
Work with industry-leading technologies and modern ML platforms, building scalable modeling and data workflows that operate
reliably at global scale.
Collaborate closely with exceptional engineers, product managers, analysts, and business stakeholders.
Continuously explore and adopt state-of-the-art methods in statistics, machine learning, and optimization, raising the
technical bar and shaping best practices across the fintech data science organization.
What you'll need:
Strong foundation in mathematics and statistics.
Bachelor’s degree in Mathematics, Statistics, Engineering, Computer Science, or a related quantitative field; Master’s
preferred; PhD a plus.
Experience or strong familiarity with experimentation frameworks, model validation, and rigorous evaluation, ideally in
high-stakes decision systems.
Proven ability to apply machine learning and statistical models in production, balancing accuracy, stability, explainability,
and real-world constraints.
Proficiency in Python for analysis, modeling, and production workflows; experience with distributed data processing (e.g.,
Spark / PySpark) is a plus.
Experience with modern ML development practices, including version control, CI/CD, and reproducible research and modeling
workflows.
Strong proficiency using AI coding agents and developer tools in a controlled, thoughtful, and production-oriented way to
accelerate development without compromising quality.
Creative, curious, and independent thinker who challenges assumptions, proposes novel approaches, and reasons deeply about
complex systems.
Excellent communication skills, able to clearly explain complex models and results to both technical and non-technical
audiences.
What We Offer:
Performance based bonus*
Attendance Bonus*
Private pension plan
Meal Allowance
Casual office and dress code
Days off*
Health, dental, and life insurance
Medicines discounts
WellHub partnership
Childcare subsidies
Discounts on Ambev products*
Clube Ben partnership
Scholarship*
School materials assurance
Language and training platforms
Transport allowance
Rules applied
Equal Opportunity & Affirmative Action:
AB InBev Growth Group is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon of
race, color, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other
applicable legally protected characteristics.
The following fields are optional, but anticipate the information for your registration*.
Remember: your data will never be used as elimination criteria in selection processes. With them, AB InBev Growth Group is able to
analyze diversity and reduce biases in selection processes. We want to contribute to changing this reality by being an inclusive
About us
AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re
number one or two in many of the world’s top beer markets, including North America, Latin America, Europe, Asia, and Africa.
About AB InBev Growth Group
Created in 2022, the Growth Group unifies our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and
Marketing teams. By bringing together global tech and commercial functions, the Growth Group allows us to fully leverage data and
drive digital transformation and organic growth for AB InBev around the world.
In addition to supporting well known global beer brands like Corona, Budweiser and Michelob Ultra, the Growth Group is home to a
robust suite of digital products including our B2B digital commerce platform BEES, on-demand delivery services Ze Delivery and
TaDa Delivery, and table top beer keg PerfectDraft.
We are an exceptional team, focused on understanding and supporting consumer and customer needs, harnessing new technology, and
scaling growth opportunities.
About BEES
At BEES, our ambition is – and always will be – to put customers at the heart of everything we do, making their lives easier and
their businesses more profitable. Through our B2B e-commerce and SaaS platform, we bring the power of digital to small and
medium-sized retailers, unlocking new growth opportunities for all.
The BEES AI organization drives data science and machine learning strategy across logistics, operations, and customer-facing
products. We build end-to-end intelligent systems that optimize how goods move through our network, improving reliability,
efficiency, and the overall customer experience at global scale.
As a member of the BEES Logistics Data Science team, you will develop data-driven solutions that power delivery planning,
operational efficiency, and customer promise accuracy across multiple markets.
What you'll do:
* Be part of a high-impact data science team building intelligent logistics systems that optimize delivery operations at a global
scale.
* Design, develop, and deploy machine learning models and optimization solutions across the full lifecycle — from research and
experimentation to production — focusing on planning, forecasting, and operational decision-making.
* Apply advanced techniques such as statistical modeling, optimization, geospatial analytics, and forecasting to improve
efficiency, reliability, and cost of delivery operations.
* Translate complex real-world logistics constraints into scalable mathematical models and data-driven systems.
* Contribute to experimentation and performance evaluation through offline analysis and online testing, ensuring solutions are
robust, scalable, and aligned with operational goals.
* Write production-grade code and build reusable data and modeling pipelines that operate reliably at scale.
* Collaborate closely with engineers, product managers, operations teams, and business stakeholders to deliver impactful
solutions.
* Drive continuous improvement by exploring new methodologies in machine learning, optimization, and applied statistics, raising
the technical bar across the organization.
What you'll need:
* Strong foundation in mathematics, statistics, and problem solving.
* Bachelor’s degree in Mathematics, Statistics, Engineering, Computer Science, or a related quantitative field; Master’s
preferred; PhD is a plus.
* Proven experience applying machine learning, optimization, or advanced analytics to real-world problems in production
environments.
* Experience with complex systems involving uncertainty, constraints, and large-scale data.
* Proficiency in Python for data analysis, modeling, and production workflows; experience with distributed processing (e.g.,
Spark / PySpark) is a plus.
* Familiarity with at least one of the following domains: optimization, forecasting, geospatial analytics, or large-scale
operational systems.
* Experience with experimentation frameworks, model validation, and performance monitoring.
* Strong understanding of software engineering best practices, including version control, CI/CD, and reproducible workflows.
* Ability to work with ambiguity, break down complex problems, and deliver practical, high-impact solutions.
* Excellent communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.
What We Offer:
* Performance based bonus*
* Attendance Bonus*
* Private pension plan
* Meal Allowance
* Casual office and dress code
* Days off*
* Health, dental, and life insurance
* Medicines discounts
* WellHub partnership
* Childcare subsidies
* Discounts on Ambev products*
* Clube Ben partnership
* Scholarship*
* School materials assurance
* Language and training platforms
* Transport allowance
*Rules applied
Equal Opportunity & Affirmative Action:
AB InBev Growth Group is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon of
race, color, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other
applicable legally protected characteristics.
The following fields are optional, but anticipate the information for your registration*.
Remember: your data will never be used as elimination criteria in selection processes. With them, AB InBev Growth Group is able to
analyze diversity and reduce biases in selection processes. We want to contribute to changing this reality by being an inclusive
company.
For more information: www.abinbev.com
Who we are
Moniepoint Inc. is Africa’s all-in-one financial platform, helping 20 million businesses and individuals access seamless payments,
banking, credit, cross-border, and business management tools each month.
As Nigeria’s largest merchant acquirer, we power most of the country’s point-of-sale (POS) transactions. Through our subsidiaries,
Moniepoint Inc. processes over $250 billion in digital payment transaction value annually.
About the role:
At Moniepoint, data is at the core of everything we do. We are a customer-centric company, and your work will enable our teams to
make informed, data-driven decisions that directly impact the success of our business. We are seeking a data-driven,
impact-oriented Senior Data Scientist to power Moniepoint’s consumer lending decisions at scale. You will build the models,
experiments, and insights that shape how we acquire, underwrite, and retain millions of customers across Nigeria and Africa.
This role is pivotal in driving our pricing, credit limit modelling, and credit model deployment strategy in a growing business
with unparalleled opportunities to give access to millions of customers. You’ll collaborate with our amazing Consumer Credit team
and drive how we think about risk ranking, product offering, and data infrastructure to create the best personalised offers for
our customers. You’ll be responsible for building our first suite of credit risk models and help drive a culture of how we should
think about machine learning vs more traditional methods - bringing fresh thinking to inspire both the team and our customers.
Sitting at the intersection of data science, credit risk, and product, you’ll translate complex data into actionable decisions
that drive growth with healthy portfolio performance.
Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation,
teamwork, and growth.
What You’ll Do
* Develop and deploy credit scoring, affordability, and behavioural models to support underwriting, pricing, and collections
* Design and run experiments to optimise approval rates, loss rates, and profitability
* Partner with product squads to embed decision logic into real-time systems
* Ensure data quality, compliance, and ethical use of models across all decisioning processes
* Mentor product squads on best practices in experimentation and data-driven decision making
* Provide models to optimise outcomes in collections, churn management and user retention
We would love to hear from you if…
* You’re comfortable with Statistics - and have a Degree or qualifications in a quantitative field (Statistics, Mathematics,
Engineering or similar)
* You have +5 years of experience in data science, decision science, or risk analytics within financial services
* Working knowledge of credit risk, consumer lending, and regulatory considerations
* Proficiency in SQL and at least one modelling/programming language (Python, R)
* Experience with A/B testing, machine learning, collections modelling and churn management
* Ability to translate complex analyses into clear recommendations for business stakeholders
* High ownership mindset and comfort working in fast-paced, cross-functional teams
What we can offer you
* Culture: We put our people first and prioritize the well-being of every team member. We’ve built a company where all opinions
carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we
are human.
* Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular
internal technical talks.
* Compensation: You’ll receive an attractive salary, pension, health insurance, monthly bonuses, plus other benefits
What to expect in the hiring process
* A preliminary phone call with the recruiter
* A coding exercise on HackerRank - covering core data science theory (math, statistics, linear algebra) and Python fundamentals
(data structures & algorithms).
* A take-home assignment
* A technical interview with a Lead in our Data Science Team to review your take-home assignment in depth
* A behavioural and technical interview with the hiring manager
Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all
employees and candidates.
Who we are
Moniepoint Inc. is Africa’s all-in-one financial platform, helping 20 million businesses and individuals access seamless payments,
banking, credit, cross-border, and business management tools each month.
As Nigeria’s largest merchant acquirer, we power most of the country’s point-of-sale (POS) transactions. Through our subsidiaries,
Moniepoint Inc. processes over $250 billion in digital payment transaction value annually.
About the role:
At Moniepoint, data is at the core of everything we do. We are a customer-centric company, and your work will enable our teams to
make informed, data-driven decisions that directly impact the success of our business. We are seeking a data-driven,
impact-oriented Senior Data Scientist to power Moniepoint’s consumer lending decisions at scale. You will build the models,
experiments, and insights that shape how we acquire, underwrite, and retain millions of customers across Nigeria and Africa.
This role is pivotal in driving our pricing, credit limit modelling, and credit model deployment strategy in a growing business
with unparalleled opportunities to give access to millions of customers. You’ll collaborate with our amazing Consumer Credit team
and drive how we think about risk ranking, product offering, and data infrastructure to create the best personalised offers for
our customers. You’ll be responsible for building our first suite of credit risk models and help drive a culture of how we should
think about machine learning vs more traditional methods - bringing fresh thinking to inspire both the team and our customers.
Sitting at the intersection of data science, credit risk, and product, you’ll translate complex data into actionable decisions
that drive growth with healthy portfolio performance.
Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation,
teamwork, and growth.
What You’ll Do
* Develop and deploy credit scoring, affordability, and behavioural models to support underwriting, pricing, and collections
* Design and run experiments to optimise approval rates, loss rates, and profitability
* Partner with product squads to embed decision logic into real-time systems
* Ensure data quality, compliance, and ethical use of models across all decisioning processes
* Mentor product squads on best practices in experimentation and data-driven decision making
* Provide models to optimise outcomes in collections, churn management and user retention
We would love to hear from you if…
* You’re comfortable with Statistics - and have a Degree or qualifications in a quantitative field (Statistics, Mathematics,
Engineering or similar)
* You have +5 years of experience in data science, decision science, or risk analytics within financial services
* Working knowledge of credit risk, consumer lending, and regulatory considerations
* Proficiency in SQL and at least one modelling/programming language (Python, R)
* Experience with A/B testing, machine learning, collections modelling and churn management
* Ability to translate complex analyses into clear recommendations for business stakeholders
* High ownership mindset and comfort working in fast-paced, cross-functional teams
What we can offer you
* Culture: We put our people first and prioritize the well-being of every team member. We’ve built a company where all opinions
carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we
are human.
* Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular
internal technical talks.
* Compensation: You’ll receive an attractive salary, pension, health insurance, monthly bonuses, plus other benefits
What to expect in the hiring process
* A preliminary phone call with the recruiter
* A coding exercise on HackerRank - covering core data science theory (math, statistics, linear algebra) and Python fundamentals
(data structures & algorithms).
* A take-home assignment
* A technical interview with a Lead in our Data Science Team to review your take-home assignment in depth
* A behavioural and technical interview with the hiring manager
Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all
employees and candidates.
