Casual Sales Assistant Jobs

About the Team DoorDash is building the world’s most reliable on-demand logistics engine for delivery! We’re looking for machine learning engineer interns to join our fast-growing engineering team to help us develop a 24x7 global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers. About the Role As a Machine Learning Engineer intern at Doordash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across Doordash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. We offer a 12-week summer internship program in our San Francisco, Sunnyvale, New York, or Seattle offices. You’re excited about this opportunity because you will… Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads,forecasting, fulfillment and search experiences at Doordash. Contribute and execute on research ideas that can be applied and used to improve product experience at Doordash. Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models. Write clean, efficient, and sustainable code We’re excited about you because you… Are working towards a Masters degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and are graduating between Fall 2027 & Summer 2028 Have a mastery of at least one systems languages (Java, C++, Python, Kotlin, GoLang) or one ML framework (Tensorflow, Pytorch, MLFlow) Have experience in research and in solving analytical problems Are a strong communicator and team player. Have a passion for applied ML and the Doordash product Ideally have

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Data Science organisation sits at the heart of Deliveroo, powering decision-making across product, commercial and operational teams through experimentation and causal inference. We’re hiring multiple Data Science Managers across different areas of the business. All of these roles are at the same level. Rather than hiring for one fixed team, we use the interview process to understand your strengths, interests and development areas, and then align you to the right scope and team at the end of the process, based on your background, interview performance, preferences and current business needs. We’re also advertising some opportunities separately where particular domain experience is especially relevant. You only need to submit one application, as we’ll consider your profile across all suitable Data Science Manager vacancies. Before an offer is made, you’ll have the opportunity to meet the proposed team, either virtually or at our London headquarters, and learn more about the role’s scope and priorities. What You’ll Be Doing You’ll own the analytical direction and measurable impact of a product or business area, while leading and developing a high-performing team of data scientists or machine learning engineers. Our Data Science Managers work across a range of consumer, product and commercial areas. Depending on the team you join, your work could focus on areas such as customer retention and loyalty, pricing and promotions, discovery and personalisation, or customer acquisition and engagement. Across all roles, you’ll lead and develop your team,

We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.) Our Mission: To actively connect people to their next great opportunity. Who We Are: ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects millions of all-sized businesses and job seekers through innovative mobile, web, and email services, as well as through partnerships with the best job boards on the web. ZipRecruiter has the #1 rated job search app on iOS & Android. Summary : We are looking for a Manager, Decision Science to lead our Enterprise Decision Science team at ZipRecruiter. The Enterprise team covers the full lifecycle of how ZipRecruiter's largest customers find, attract, and hire talent. That runs from the performance marketing campaigns that drive traffic, to the apply experience and ATS integrations, to the signals that help employers identify the best candidates. As a Manager of the Enterprise Decision Science team, you will be a true player-coach: developing a small team of decision scientists while personally leaning in on strategic analyses in your problem space. You can bring rigor to evaluation in a space where clean experiments are rare and the data is sometimes too thin for formal causal methods. You know when to reach for a quasi-experimental design and when to build a well-reasoned recommendation from directional data and qualitative signals and communicate recommendations clearly to Product, Engineering, and GTM partners. Key Focuses: Lead & Develop the Team: Manage and coach a team of decision scientists supporting the Enterprise area. Review and coach on their work, own performance and career development conversations, set clear expectations, and help each person build on their strengths and grow their business and technical skills. Prioritize across multiple concurrent projects, al

Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Data Scientist II - Decision Science Using data, you will play a crucial role in driving decision-making and delivering impactful insights to our stakeholders. You will apply advanced analytical techniques, build Machine Learning (ML) models, and use experimentation and causal inference methods to solve sophisticated business problems related to platform engagement, product features, and games. What you’ll be doing: Apply advanced statistical and ML techniques to analyse large and complex datasets, extracting actionable insights in a commercial setting. Apply your knowledge of Experimentation, Causal Inference, ML, and statistical modelling to develop robust predictive models and identify causal relationships. Collaborate with cross-functional teams to define business problems, formulate hypotheses, and design experiments to test them. Independently extract and integrate data from multiple data systems, including writing complex SQL queries, to support analytical efforts. Support the delivery of results and presentations to stakeholders, translating complex analyses into clear and actionable recommendations. Stay up to date on the latest advancements in Data Science, including Causal Inference, Gen AI, and ML, and share knowledge and new ideas with the team. What

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: US remote-friendly or any office location - SF, LA, CHI, NY The Data Science Team at Reddit is growing and we are looking for experienced Data Scientists to partner with our cross-functional partners (Product, Engineering, Designer, Marketing, Business Development etc.) to help us build and improve the systems that continuously drive our user and revenue growth. As a Senior Data Scientist on the team, you will have the opportunity to play a significant role in driving the success of key product areas at Reddit (Consumer, Ads, Safety etc.). You will lead and contribute to defining the product strategy through measurement and metrics design, experimentation and causal analyses, supporting product decisions via deep data analyses, and research. This person will be an industry technical leader with a solid technical background, strong business acumen, and excellent cross-functional stakeholders management skills. You will go through a general Data Scientists hiring process and get matched to the product area that best fits your background and interest. Responsibilities: Develop action-oriented insights to drive the product strategy through observational causal analysis and experiment meta-analysis, and clearly communicate results to stakeholders up to the C-suite to take action based on the recommendations Uplevel experimentation practices on the team through guiding design, execution, and deep dive analyses to maximize learnings from A/B tests Create new ETLs, tables, dashboards, and other self-

About Supabase Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. About the Role We're looking for a Senior Data Analyst, Marketing to join our Data Intelligence team and build the measurement foundation that tells us what's actually working across paid and PLG channels. You'll work closely with Marketing, Growth, and channel owners, helping us move past platform-reported metrics and vanity numbers into causal, trusted answers about what drives pipeline and revenue. This role is ideal for someone who thrives in async, fast-paced environments, is AI-forward in how they work, and is excited about building a measurement function from the ground up. What You'll Be Responsible for Marketing Measurement Strategy Own the end-to-end marketing measurement strategy across experimentation, media mix modeling, and attribution for paid and PLG channels Establish and evolve the attribution framework: how platform data, multi-touch attribution, MMM, and experiments work together to inform decisions Translate complex measurement outputs into clear recommendations on where to invest, what to cut, and how to hit pipeline, revenue, and efficiency targets (CAC, payback, LTV to CAC) Serve as the subject matter expert for marketing measurement, educating stakeholders on causality, model uncertainty, and the limitations of platform-reported metrics Incrementality and Experimentation Design and run always-on incrementality tests, user-level and geo-level, to quantify the causal impact of key channels, campaigns, and tactics Calculate incremental lift, incrementality percent, and incremental ROAS/CPA, and use these to guide budget reallocation Build repeatable analysis templates and playbooks for experiment design, analysis, and readouts so results are consistent across teams Partner

Asana's Data Science team helps us fulfill our mission by informing strategy, defining success metrics, and identifying new ways to deliver user value . Data scientists are at the crux of deepening our understanding of the customers and driving more business outcomes by leveraging experimentation, causal inference, statistical and machine learning techniques, and data storytelling . As an Analytical Engineering Manager, you lead a team of Analytical Engineers who own the data foundations for the business: the Gold layer, canonical metrics, certified dashboards, and semantic layer that make Asana's most important numbers trustworthy, and that make AI-powered self-serve through Claude and Databricks Genie actually work. You sit at the intersection of Data Engineering, Analytics, and Data Science, and you are accountable for whether business stakeholders trust the data in your team's domains and can answer their own questi ons without routing through your team. This role is based in our Warsaw office with an office-centric hybrid schedule . The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements . We offer a Contract of Employment (UoP) for our employees in Poland. What you’ll achieve Lead, grow, and develop a team of Analytical Engineers: Own hiring, coaching, performance, and career growth, setting a high bar for data-model quality and stakeholder trust. Own the Gold layer and semantic-layer strategy across your team's domains (e.g. PLG, marketing, revenue, NPI/AWM), taking accountability for curated data models, canonical metrics, dashboards, and Genie spaces. Treat every recurring insight as a product with an owner, a cadence, and an SLA, building a catalog of trusted, versioned data products instead of one-off rebuilds. Drive self-serve enablement by prioritizing Go

Data Scientist The Data Science team helps us fulfill our mission by informing strategy, defining success metrics, and identifying new ways to deliver user value . Data scientists are at the crux of deepening our understanding of the customers and driving more business outcomes by leveraging experimentation, causal inference, statistical and machine learning techniques, and data storytelling . We understand our company’s goals and proactively inform their direction with data so that our product can help more teams do great things. As a Data Scientist at Asana, you’ll help us ask the right questions and answer them rigorously. You’ll work closely with our Pro duct and Business teams to understand their goals and proactively inform their direction with data. You’ll keep taking on new responsibilities as you grow—from defining core metrics to building machine learning models and keeping the data flowin g in our pipelines This role is based in our Warsaw office with an office-centric hybrid schedule . The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements . We offer a Contract of Employment (UoP) for our employees in Poland . What you’ll achieve Design and analyze experiments to measure the impact of new product features. Investigate high-level questions like “What are the collaborative patterns of the most successful teams using Asana?” Add new metrics and aggregations to our data warehouse to make new classes of questions answerable. Build models to predict the growth trajectory of different customer segments. Partner with cross-functional stakeholders across engineering, product management, and business teams to drive data-informed decision-making. About you Bachelor's Degree in Computer Science, Math, Statistics, Engineering, a related quantitative field, or equivale

Welcome systems thinkers. System builds software to help the world see and solve anything as a system, starting in healthcare. We are a Public Benefit Corporation driven by purpose and shaped by values. We hire systems thinkers who are motivated by our purpose, share our values, and have the skills to advance our mission. At System, research is the origin of our most important ideas — and researchers work at the frontier of graph theory, clinical AI, causal inference, and knowledge representation to push the boundaries of what our platform can do. As a researcher at System, you will: Develop and validate novel methods for modeling complex, interconnected systems Work at the intersection of graph theory, machine learning, and domain-specific knowledge Collaborate with Data Science and Engineering to transition research findings into production Publish and present findings that advance both the field and System's mission Partner with clinical and domain experts to ground research in real-world impact Contribute to a culture of intellectual rigor, curiosity, and continuous learning The ideal candidate has: Master's or PhD in Computer Science, Statistics, Biomedical Informatics, or a related field A strong publication record or equivalent applied research experience Deep expertise in machine learning, statistical modeling, or computational methods Experience working with complex, heterogeneous, or graph-structured data Ability to communicate research findings clearly to both technical and non-technical audiences Comfort operating in a fast-paced startup environment alongside a long research horizon Bonus if you have: Experience with clinical NLP, EHR data, or healthcare ontologies (SNOMED, ICD, OMOP) Familiarity with knowledge graphs, semantic web technologies, or ontology engineering Background in causal inference, systems dynamics, or complex adaptive systems Experience collaborating with clinicians, policymakers, or public health researchers You might be

About the Team The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across the company. We partner closely with product, engineering, and infrastructure teams to ensure experiments are trustworthy, statistically rigorous, and scalable to the needs of frontier AI products. Our mission is to help teams make better decisions through reliable experimentation. We care deeply about statistical correctness, pragmatic solutions, and building systems that researchers and engineers can trust at massive scale. The team operates at the intersection of experimentation methodology, data infrastructure, causal inference, and product analytics. We are looking for experienced experimentation experts who want to shape the future of experimentation in the AI era. About the Role We are hiring a Staff-level Data Scientist to help lead the evolution of OpenAI’s core experimentation platform. This role is focused on improving the statistical rigor, reliability, and practical usability of experimentation across the company. You’ll work on some of the hardest problems in online experimentation: sample ratio mismatch detection, variance reduction, bias mitigation, metric design, triggered analysis, heterogeneous treatment effects, sequential testing, and experimentation in complex ML systems. You’ll also help translate advanced statistical concepts into pragmatic systems and product experiences that teams can actually use. This is a highly technical individual contributor role with significant influence across methodology, platform architecture, and experimentation best practices. The ideal candidate combines deep statistical expertise with strong systems intuition and hands-on experience building or operating experimentation platforms at scale. In this role, you will: Drive the statistical direction and technical strategy for OpenAI’s experimentation platform Design and improve experimentation methodolo

Job ID: 111268 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. Responsibilities: Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context. Perform exploratory data analysis to gain a deeper understanding of the problem. Construct and fit statistical, machine learning, or optimization models. 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; facilitate launch decisions. Experience: Education and Experience: Master's degree or foreign equivalent in Business Analytics and Information Management, Data Science, or related field. 2 years of experience in job offered, operations research, or related occupation. Skills: Experience creating metrics and analytical tools to track and monitor growth. Experience with statistics, machine learning, causal inference, data scientific forecasting, and authoring data pipelines. Experience with building and evaluating optimization and inference models, and predictive modeling. Experience with writing production quality computer code and using MATLAB, R, and Python. Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible Subsidized commuter benefits Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program Lyft is

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 is an integral component of Coinbase’s product and decision making process: we work in partnership with Product, Engineering and Design to influence the roadmap and better understand our users. With a deep expertise in experimentation, analytics and advanced modeling, we produce insights which directly move the company’s bottom line. What you'll be doing: Conduct analysis and deep dives on ambiguous problems for our business. Your work will result in insights and recommendations that guide the team’s decision making. Build, tune, or measure the performance of online and offline ML models and AI systems used across Coinbase. Act as owner for a broad scope of data and metrics, from definitions and core logging to presentation of data visualizations. Guide code reviews, provide SQL and Python expertise, and create well-maintained ETL jobs. Maintain a high bar for statistical rigor on your team. Design, execute, and uplevel experimentation and causal analyses that build confidence with your stakeholders. What we look for in you: A BA/BS in a quantitative field (ex Math, Stats, Physics, or Computer Science) with ≥5+ years of relevant experience or a PhD in a quantitative field with with ≥3+ years of relevant experience Demonstrated experience in driving impactful data science projects that tackle ambiguous problem spaces. Ability to in

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. About the role We’re looking for a VP, Statistical Measurement to lead statistical methodology, measurement standards and quantitative quality across our Open Intelligence Solutions (OIS) portfolio. This is a senior leadership role within Strategic Data Science, focused on ensuring that the analytical work we produce is rigorous, credible and commercially meaningful . You’ll be the organisation’s authority on statistical methodology and numerical quality, helping teams turn complex data into robust evidence that clients and senior stakeholders can trust. You’ll shape the evolution of Marketing Mix Modelling (MMM), attribution, incrementality, causal inference and experimental design , while establishing consistent standards for validation, statistical quality assurance and communicating uncertainty. You’ll also play an important role in preparing the organisation for an increasingly AI-assisted analytical environment , ensuring that both people and AI-enabled workflows apply statistical methods responsibly and communicate findings accurately. What you’ll do Own statistical methodology and measurement

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is looking for an experienced Senior Data Scientist to drive help guide analyses, create predictive and prescriptive insights, and influence decisions. With thousands of subscribing organizations and millions of users there is lots of opportunity to make a meaningful impact and increase growth through analytics within Smartsheet. You are curious, have strong data science and machine learning skills and the ability to communicate key insights effectively. You will work primarily with Product teams and will be a part of Smartsheet's Business Intelligence team. This full-time position reports to the Sr. Director of Data Science and can be located in our Bellevue, WA office, or you may work remotely from anywhere in the US where Smartsheet is a registered employer. You Will: Leverage data analytics and machine learning techniques to inform product development, optimize user experiences, and drive key performance metrics such as user acquisition, engagement, retention, and growth Partner with Product, UX and Engineering teams, understand their goals, and execute on opportunities to draw relevant insights and drive tangible impact Understand our customer needs and design metrics to analyze how our customers are using product and optimize products and features Conduct experiments, causal studies and A/B tests to measure the impact of product changes Leverage data to understand product performance and to identify improvement opportunities Complete the full analytics lifecycle from understanding the busines

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. Why Data Science And Engineering The Data Science & Engineering organization's mission is to increase our speed, frequency, and acumen in making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum, including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling, and machine learning. Aligned and partnering with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products, and measure impact on our community of players and developers. In Data Science & Engineering, you will build the macroeconomic models, simulation frameworks, and policy mechanics that scale Roblox’s virtual economy. By analyzing Robux currency dynamics, global pricing strategies, and developer exchange policies, your work will directly inform strategic decision-making, financial policy, and executive roadmaps on our road to connecting one billion users. You will: Develop, build, and refine macroeconomic models to forecast and monitor Robux money supply, velocity, inflati