Data Scientist Algorithms Community Support in Singapore

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Our Growth team is on a mission to acquire, convert, and grow millions of merchants globally across the full Stripe suite of financial products. We're a cross-functional team of engineers, scientists, marketers, designers, and product managers that deliver the insights, algorithms, internal systems and tools, and user-facing experiences that fuel our growth. We help businesses around the world find Stripe, get started, and grow. As part of the Growth Engineering team, you'll build the systems, products, internal tools, and customer-facing experiences that power intelligence behind our go-to-market and product-led growth. This includes building ML-powered recommendations and growth experimentation engines, multi-channel notification systems, and key growth-related customer experiences (e.g., onboarding flows, user dashboards, product recommendations). What you'll do As a full-stack engineer on the Growth team, you'll build and ship experiments and product improvements across stripe.com and the Dashboard to help businesses find and get started on Stripe. You'll work on critical parts of the funnel for self-serve users, ensuring their experience on Stripe is consistently high-quality. With other engineers and data scientists, you'll turn ML-powered recommendations, messaging, and experimentation into impact that moves company metrics. Responsibilities Build and maintain scalable systems and customer experiences that help businesses discover, on

DATA SCIENTIST — Fab 10A, Singapore. Apply via Workday.

DATA SCIENTIST, SMAI — MSB, Singapore. Apply via Workday.

Data Scientist — Fab 10A, Singapore. Apply via Workday.

DATA SCIENTIST, SMAI — MSB, Singapore. Apply via Workday.

DATA SCIENTIST — Fab 10A, Singapore. Apply via Workday.

DATA SCIENTIST — Fab 10N/X, Singapore. Apply via Workday.

DATA SCIENTIST — Fab 10A, Singapore. Apply via Workday.

Data Scientist — Fab 10A, Singapore. Apply via Workday.

DATA SCIENTIST, SMART MFG & AI — Fab 10A, Singapore. Apply via Workday.

Data Scientist — Fab 10A, Singapore. Apply via Workday.

DATA SCIENTIST — Fab 10A, Singapore. Apply via Workday.

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background. What you’ll do We’re looking for a Data Scientist to partner with our Global Growth teams. You’ll play a key role in designing and shipping experiments, as well as identifying improvement opportunities across stripe.com and the dashboard to help businesses worldwide get started on Stripe. You’ll help us understand, grow, and optimize the self-serve user funnel to ensure a consistently high-quality onboarding experience for users globally. As Data Scientists at Stripe, our mission is to ensure that company strate

Data Scientist — MSB, Singapore. Apply via Workday.

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Data Science sits at the heart of how Coinbase builds products and makes decisions. We partner with Product, Engineering, and Design to shape roadmaps, understand our users, and move the company's bottom line through rigorous experimentation, analytics, and advanced modeling. As a Data Scientist on the Consumer team, you'll improve the customer experience across Coinbase's consumer products — including spot and advanced trading, yield, Coinbase One, international expansion, and new launches such as prediction markets and equities trading. You'll define key metrics, build measurement and causal frameworks, and translate insights directly into product strategy and shipped improvements. What you'll do: Drive analysis and deep dives on ambiguous business problems, delivering insights and recommendations that guide team decision-making Own a broad scope of data and metrics — from core logging to polished data visualizations Lead code reviews, contribute SQL and Python expertise, and maintain reliable ETL pipelines Uphold a high bar for statistical rigor, ensuring experimentation and causal analyses build genuine confidence with stakeholders Required Skills and Experience: BA/BS in a quantitative field (Math, Stats, Physics, CS, or similar) with 5+ years of relevant experience, or a PhD with 3+ years of relevant experience Proven track record of delivering impa