Data Instructor Jobs

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma’s Data Science team partners across product, engineering, design, marketing, sales, and operations to help Figma make better decisions with data. As an intern on our team, you'll work on technical challenges that have real impact on our product and business, and we're looking for interns with strong foundations in coding and statistics and who are clear communicators with both technical and non-technical audiences. This internship will be based out of our San Francisco or New York Hub. What you'll do at Figma: Own a scoped project end to end—from framing the question with Product, Engineering, Design, and Data Science partners through delivering the work—with support from a manager and mentor. Analyze user behavior, product performance, or business data to uncover insights and translate them into recommendations for businessDesign and evaluate experiments and develop metrics that help teams understand the impact of product changes.Build models to understand user behavior and predict growth Build and improve data pipelines and tools that make product data more scalable and accessible Focus areas may include analytics, experimentation, or infrastructure - based on your interests and business needs Some projects you could work on: Analyze how people adopt and use a new or existing Figma product experience, define meaningful success metrics, and turn patterns in engagement and retention into product recommendations. Build and validate a new analytical method

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Data Engineering Team Our Data Engineering team is part of the Technology Data & Intelligence organization, on a mission to accelerate Okta’s scale and growth. We focus on building platforms and capabilities utilized across the organization by sales, marketing, engineering, finance, product, and operations. You will be part of a team performing detailed technical designs, development, and implementation of applications using cutting-edge technology stacks. The Senior Data Engineer Opportunity As a Senior Data Engineer, you will be responsible for designing, building, and maintaining scalable solutions. This role involves collaborating with data engineers, analysts, scientists, and other engineers to ensure data availability, integrity, and security. You will play a critical role in preparing Okta for its AI-driven future by building stable data layers and partnering with Analytics Engineers to power our AI/ML systems. What you’ll be doing D

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. We are the Data team within Plaid’s Fraud organization. We build the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s network data to help identify and prevent fraud before it happens. Our team owns the end-to-end ML lifecycle, from feature pipelines and model training to production serving and monitoring, ensuring our systems are reliable, scalable, and built to support hundreds of customers and data partners. As a Data Scientist on the Fraud Data team, you will analyze customer and network traffic to understand how Plaid Protect performs across a range of use cases and customer segments. You’ll build dashboards and metrics that provide a clear, shared view of product performance, run backtests to evaluate performance and identify high-impact rules and model strategies, and generate insights that support customer growth and expansion. You’ll also design scalable data models and schemas to enable reliable analysis and reporting, while partnering closely with Product and Engineering to design and analyze experiments for new customer-facing features. Responsibilities: Work at the intersection of product analytics, machine learning, and fraud a

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Fraud Data is the data science and machine learning team within Plaid’s Fraud organization, responsible for using data and ML to improve and scale Plaid’s fraud products. Within Fraud Data, the Customer & Product Intelligence team focuses on understanding product performance, uncovering customer insights, and enabling go-to-market teams with data-driven solutions. The team partners closely with customers and GTM teams on fraud analyses and proofs of concept, turning customer learnings into scalable, reusable product capabilities. We also build the metrics, analytics, and data foundations that measure product health, identify opportunities for improvement, and guide product decisions across Plaid’s Fraud portfolio. As a Data Science Manager, you will lead a team responsible for customer-facing data science and Fraud product analytics. You will set the team's roadmap, develop its data scientists, and remain involved in analytical methods, technical reviews, and customer investigations. You will: Set a 6–12-month roadmap with Product, Engineering, and GTM, and assign priorities and responsibilities across the team. Define product metrics, their underlying data, and reporting and

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data and analytics are at the heart of Lyft’s products and decision-making. As a member of the Lyft Urban Solutions team, you will play a key role in shaping the future of bikeshare by leveraging data to operational needs and city partners. In this role, you will collaborate closely with Operations, Science, and Finance teams to drive data-driven strategies that align our operations with city transportation goals. You will work in a fast-paced environment where analytical insights directly impact fleet management, operator performance, pricing, rider accessibility, and long-term investments in bikesharing infrastructure. We’re looking for a passionate and driven Data Analyst Intern to tackle some of the most complex and impactful challenges in bikesharing. If you’re excited about shaping the future of urban mobility through data, we’d love to hear from you. Responsibilities: Partner with Operations, Engineering, Data Science & Analytics, Product, Finance and other cross-functional stakeholders to manage and update key business logic Develop frameworks and scalable processes to streamline reporting, drive decision-making and prioritization Define the metrics used to measure the success of strategic initiatives and system health; build dashboards to monitor metrics performance over time Work closely with cross-functional partners to deliver data quickly, reliably and accurately to our city partners Monitor and diagnose KPI performance and present findings to senior leadership Experience: Currently pursuing a Bachelors or Masters degree in mathematical sciences (Operations Research, Computer Science, Statistics, Applied Mathematics, Theoretical Physics, Behavioral Science, Electrical Engineering, etc.), Economics (Microeconomics Theory, Econometrics etc.), Data Engineering; or a related field;

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Interns work side-by-side with top engineers in the industry while having autonomy from the get-go. They contribute to user-facing products and are able to see their work go live quickly. Lyft fosters a collaborative environment in the office, so there's always a sharp mind eager to hear about your next idea. So what's yours? Responsibilities: Own your project, while checking in with other team members throughout the day with questions and updates You leave the code in a better state than when you found it (progressive refactor) You value reliability, ensured by testing Participate in code reviews to ensure code quality and distribute knowledge Continuous integration and deployment Go home knowing that your work today is meaningfully improving the lives of every Lyft driver and every Lyft passenger! Experience: Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science or related major from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required) . For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for an internship in Toronto Strong knowledge of CS fundamentals Knowledge of SQL and data modeling fundamentals Experience working with databases Excellent communication skills Interest in solving large scale data problems in a real world scenario Passion for community, sustainability, and/or transportation Benefits: Mental health benefits In addition to holidays, interns receive 2 days paid time off and 3 days sick time off Subsidized commuter benefits and Lyft ride credits Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft belie

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree in mathematical sciences ( Operations Research, Computer Science, Statistic

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree in mathematical sciences ( Operations Research, Computer Science, Statistic

Reolink , a leader in intelligent visual technology for homes and businesses, was founded in 2009 by a group of engineers with a strong commitment to and passion for smarter security solutions. Our products are now trusted by millions of users across more than 110 countries and regions worldwide. Building on this trust, we continue expanding our presence and bringing our innovations to more markets around the globe. Reolink remains committed to delivering advanced, reliable, and user‑centric solutions that empower people to protect what matters most. Position: E-commerce Data Analysts 5 Work Days Per Week Office Near Tai Seng MRT, Singapore Medical Benefits Provided Entitled to Yearly Bonus & Performance Bonus Background of E-Commerce Team Our e-commerce platform focus on Reolink Official Website & Amazon for different region particularly for the Australia and Europes & United States. Responsible driving business decisions through data analysis and visualization, job scopes include: Driving actionable insights: Analyzing data to generate insights that improve performance, profitability, and guest experience across various e-commerce platforms. Data analysis and reporting: Building data pipelines, self-service dashboards, and developing new in-house API features to drive growth and extend reach into other ecosystems/platforms. Collaboration with teams: Working with product management, engineering, and design teams to ensure data-driven decisions align with business goals. Data quality and integrity: Validating data quality, investigating data issues, and collaborating with data engineering teams to improve data pipelines and definitions. Supporting business decisions: Providing professional data support for business product decisions in e-commerce scenarios and building an e-commerce product metric system. E-commerce Data Analysts play a crucial role in the e-commerce industry, leveraging data to enhance business strategies a

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 Data Science at Stripe is a vibrant community where data analysts and data scientists learn and grow together. You'll work with some of the most fundamental data at Stripe, and use that data to help drive company-wide initiatives. We have a variety of Data Analytics roles and teams across Stripe and Data Analysts are hired in line with the business needs and domain of the organization they will support. What you’ll do We’re looking for a Data Analyst to partner with Stripe’s Global organization, helping millions of users sell around the world. You’ll help build analytics and data products for solutions such as Adaptive Pricing and Stripe Managed Payments, as well as Stripe’s expansion into new markets across LATAM and EMEA. Responsibilities Design and build scalable data models and infrastructure to power product analytics and metrics reporting as we launch and grow new products Own business-critical data products, including Tier-1 datasets and production pipelines, ensuring reliability through rigorous testing, monitoring, and documentation Build and maintain the metric definitions, metadata, and business context that enable AI agents to help stakeholders explore trusted data and answer business questions independently Develop dashboards, automated reporting, and thoughtful analyses to surface actionable insights and proactively identify business opportunities Partner closely with senior business leaders to translate business needs into ana

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE This is a sourcing-first role, not a deal-closing role. Baseten needs someone who can build and maintain deep relationships across the long tail of data center and powered land providers, well beyond the handful of large, well-known players that everyone in the market is already competing for. This coverage area is a key differentiator for Baseten's broader compute strategy, so we're looking for the best possible person in this specific lane rather than a generalist. You'll own the full lifecycle of a sourcing relationship — from first outreach to ongoing management — not just the introduction. WHAT YOU'LL DO Build and maintain a comprehensive map of data center and powered land opportunities, with a particular focus on the long tail rather than the handful of major, oversubscribed players Own the full sourcing lifecycle for each relationship — from identifying and reaching out to new providers, through negotiation support, to ongoing relationship management — not just the initial introduction Develop and manage sourcing relationships across neoclouds, hyperscalers, brokers, and independent operators Quickly and independently evaluate new sites and spaces to determine fit and priority Prepare business cases and cost analysis to support new data center and powered land opportunities, partnering with Finance where needed Maintain accurate records of suppliers, contracts, and commercial terms so the team has a reli

Qui sommes-nous ? Fondée en 2014, Artefact est une société française de services autour de la data, spécialisée dans le conseil en IA, transformation data et en data & digital marketing. L’approche unique d’Artefact, qui fait le pont entre la donnée et le business, permet à nos clients d’atteindre leurs objectifs business de façon dédiée et efficace. Nos 2500 collaborateurs répartis dans 27 bureaux à travers le monde allient leurs compétences pluridisciplinaires au profit de l’innovation business des entreprises. La mission des Artefactors ? Transformer la data de nos clients en impact business. Dans ce sens, nous collaborons avec plus de 1000 clients, leaders de leurs industries (Orange, Carrefour, Samsung, AccorHotels, L’Oréal, LVMH, Decathlon) et sommes partenaires privilégiés de Google (GMP/GCP), AWS ainsi que Microsoft Azure. En tant que stagiaire Data Analyst, tu seras intégré(e) à une équipe travaillant étroitement avec des consultants / data scientists et tu participeras à des missions ayant un impact réel pour les clients. Tes missions pourront inclure : Collecter, nettoyer, préparer les données à partir de sources diverses (bases de données internes, API, logs, etc.). Explorer et analyser les données pour identifier tendances, anomalies, corrélations, patterns utiles. Participer à la conception et réalisation de dashboards / reportings sous outils de data visualisation (ex. Tableau, PowerBI, ou outils internes) pour présenter les résultats aux équipes ou aux clients. Contribuer à la définition de KPI pertinents selon les objectifs métier. Travailler en collaboration avec les équipes métier (marketing, produit, etc.) pour bien comprendre leurs besoins et transformer ces besoins en analyses exploitables. Aider à automatiser certains processus de reporting ou analyses simples. Documenter tes travaux, partager les résultats et les apprentissages au sein de l’équipe, proposer des améliorations ou de nouvelles approches quand c’est possible. Profil recherché

CAPCO POLAND *We're looking for candidates located in Poland Capco Poland is a global technology and management consultancy specializing in driving digital transformation across the financial services industry. We are passionate about helping our clients succeed in an ever-changing industry. We also are: Experts in banking and payments, capital markets, wealth and asset management Focused on maintaining our nimble, agile, and entrepreneurial culture Committed to growing our business and hiring the best talent to help us get there Role Overview: At Capco, we combine business, data and technology expertise to deliver meaningful transformation across financial services. We are looking for a Data Business Analyst to support a large-scale banking data initiative. This role sits at the intersection of business requirements, data analysis and technical delivery , with a strong focus on translating business needs into well-defined data solutions. You will be responsible for an end-to-end analytical scope: understanding data requirements, identifying and validating source data, defining business logic and mappings, preparing Asset Designs and implementation-ready requirements, and collaborating with Data Engineering teams throughout delivery. This is a great opportunity for someone who enjoys combining hands-on data analysis with business analysis and solution design in a complex banking environment. What You'll be responsible for: Gathering, analysing and refining business and data requirements and translating them into clear technical requirements. Acting as a link between business stakeholders, data teams, architects and Data Engineers throughout the data delivery lifecycle. Identifying relevant data sources across HDP/Hadoop environments and determining how they should be delivered to the analytical layer in Google Cloud Platform . Analysing and validating data using SQL, BigQuery, Hive and Spark SQL . Preparing and maintaining Asset Designs, data mappings and deta