Organization: StubHub, www.stubhub.com (an eBay company NASDAQ: EBAY) The Opportunity We are looking for an experienced Data scientist with exceptional product sense to help champion the use of data in product decision-making. In this role you will work closely with our Engineering, Product, Ops, and Design teams to evaluate product opportunities, track product metrics, develop and analyze experiments, and drive deep-dive studies to identify new opportunities. You will: Apply data & analytical skills to help understand how our customers use our products Partner closely with product leadership to define, measure and report on core product and feature metrics Design customer-facing experiments (A/B tests) and distill their results into actionable outcomes Execute cohort studies and drive analyses to understand customer behavior and identify opportunities for improving our product(s) Collaborate with data and business intelligence teams to develop reports and visualization dashboards Build financial models to project key business metrics - Traffic, conversion, Engagement - and develop KPIs to measure initiative performance You have: Strong quantitative background with Product analytics experience. Proven track record in solving business problems through fact based and scientific analytics Excellent technical skills - including the ability to query databases (SQL, Hive etc.), leveraging R/Python to analyze complex data, and using Tableau (or other visualization tools) to deliver insights at scale Deep understanding of statistics, experimental design, and causal inference The ability to translate analytical insights into clear recommendations and effectively deliver it to technical and non-technical stakeholders Worked in cross-functional and cross-cultural teams, and are able to communicate technically intricate concepts/results in business terms Passion for technology and consumer products Why StubHub? StubHub is the world's largest ticket marketplace, enabling fans to buy and sell tickets to tens of thousands of sports, concert, theater and other live entertainment events. StubHub reinvented the ticket resale market in 2000 and continues to lead it through innovation. The company's unique online marketplace, dedicated solely to tickets, provides all fans the choice to buy or sell their tickets in a safe, convenient and highly reliable environment. All transactions are processed and delivered by StubHub and backed by the company's FanProtect Guarantee™ processing a ticket every second today with billions of ticket sales each year globally. Company partners MLB, AEG, ESPN and many leading teams such as the San Francisco Giants and University of Texas, along with over 60 other teams in MLB, NBA, NHL and NCAA. Our Values StubHub One – We act as one team in pursuit of connecting people through inspiring event experiences At StubHub, we are: Driven – We strive for excellence – constantly improving our game Courageous – We are bold & not afraid to challenge the status quo Inventive – We see what others don’t & pioneer new paths Richly Diverse – We recognize & respect everyone as a unique individual Brand – We experience the world through StubHub. eBay Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us. We will make every effort to respond to your request for disability assistance as soon as possible.

eBay is diversifying payments, this role will be power Payments ecosystem by providing insights to executive leadership, analytics related to fraud solutions, value proposition and innovation related to the overall customer experience for eBay! Looking for a company that inspires passion, courage and imagination, where you can be part of the team shaping the future of global commerce? Want to shape how millions of people buy, sell, connect, and share around the world? If you’re interested in joining a purpose driven community that is dedicated to creating an ambitious and inclusive workplace, join eBay – a company you can be proud to be a part of. The Global Payments, Billing & Risk (GPBR) function at eBay works to ensure great experiences when buyers and sellers come together and engage in commerce on the biggest marketplace in the world. This involves comprehensively understanding Payments & Risks on eBay. Identifying the opportunity areas and helping build scalable solutions to drive great user experience. Analytics is a critical need for each area. Core analytics capabilities include the ability to instrument right KPI’s, identify the landscape of entire function, figure out opportunities for improvement work with product and payment providers to craft scalable solutions, and monitor their performance. The GPBR Analytics and Insights team builds this behavioral intelligence by exploring innovative interpretations of existing and new sources of data, using advanced analytical techniques, and overlaying the appropriate strategies to deliver world-class results. The group is multi-disciplinary with broad spectrum of industry experiences and deep analytical and quantitative expertise. The group is currently seeking a high energy, driven, collaborative team member that brings extensive problem solving skills to further its goal of applying cutting-edge analytics, Insights and visualization to drive payments roadmap. The role is data and analytically intensive. Successful candidates should be quick learners, strategic thinkers, operational and execution driven facilitators, problem solvers, and have an entrepreneurial spirit. This role is heavily cross-functional and ideal for candidates who enjoy both defining and solving complex problems, while getting deeply involved in the classification domain and product partners. Skills in problem definition, rigorous analysis, and recommendation development will also be critical as well as demonstration of exceptional interpersonal skills, initiative and integrity. Responsibilities Develop a deep understanding of Payments ecosystem and associated risks. Model seller and buyer risk for the market place business Structure complex, ambiguous business questions and utilize analytical skills to synthesize actionable insights to the benefit of leaders in the organization Discover new opportunities to grow and optimize the business through analytics, financial modeling, and business case development. Own the domain and associated deep dive analytics. Design, plan, and execute methodologies to measure successes of business initiatives. Collaborate with other analysts/data scientists and help guide strategy based on learning from other analyses/projects across the organization Perform analysis, hypothesis testing, build risk strategy and policy recommendation. Conduct product performance A/B test analysis. Create and maintain insightful automated reports and dashboards utilizing typical data quality functions (e.g. standardization, consistency, etc.) Work closely across the matrix with teams like Finance, Marketing, Product, Engineering and senior executives Qualifications Bachelor’s degree in Computer Science, Engineering, MIS or other quantitative fields 5+ years’ of professional experience in using data to facilitate business decisions Extensive experience in BI/DW best practices Experience in efficient manipulation and analysis of large data sets Proficiency in databases (SQL), and programming languages (at least one of following: Python, R, Ruby, Java, etc) Exceptionally attentive to detail and embracing of teamwork People-oriented; eager to build positive and productive relationships with a variety of stakeholders Experience manipulating large data sets, interpreting data trends and using a multitude of disparate data sources and tools Ability to shift priorities quickly, while maintaining a high degree of organization and control eBay Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us. We will make every effort to respond to your request for disability assistance as soon as possible.

Overview Come join Intuit as a Principal Machine Learning Engineer! Responsibilities In this role, you’ll be embedded inside a vibrant team of data scientists. You’ll be expected to help conceive, code, and deploy data science models at scale using the latest industry tools. Important skills include data wrangling, feature engineering, developing models, and testing metrics.  You can expect to... Discover data sources, get access to them, import them, clean them up, and make them “machine learning ready”. Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models. Partner with data scientists to understand, implement, refine and design machine learning and other algorithms. Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your models. Work cross functionally with product managers, data scientists and product engineers, and communicate results to peers and leaders. Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver. Qualifications BS, MS, or PhD degree in Computer Science or related field, or equivalent practical experience. Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark). Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering). Understand machine learning principles (training, validation, etc.) Knowledge of data query and data processing tools (i.e. SQL) Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning). Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code. Mathematics fundamentals: linear algebra, calculus, probability Preferred Additional Qualifications: Interest in reading academic papers and trying to implement state-of-the-art experimental systems Experience using deep learning architectures Experience deploying highly scalable software supporting millions or more users Experience with GPU acceleration (i.e. CUDA and cuDNN) Experience with integrating applications and platforms with cloud technologies (i.e. AWS and GCP) Experience with NLP and NLU Imagine a career where your creative inspiration can fuel BIG innovation. Year-over-year, Intuit has been recognized as a best employer and is consistently ranked on Fortune's "100 Best Companies To Work For" and Fortune World's "Most Admired Software Companies" lists. Immerse yourself in our award winning culture while creating breakthrough solutions that simplify the lives of consumers and small businesses and their customers worldwide. Intuit is expanding its social, mobile, and global footprint with a full suite of products and services that are revolutionizing the industry. Utilizing design for delight and lean startup methodologies, our entrepreneurial employees have brought more than 250 innovations to market – from QuickBooks® and TurboTax®, to GoPayment, Mint.com, big data, cloud (SaaS, PaaS) and mobile apps. The breadth and depth of these customer-driven innovations mean limitless opportunities for you to turn your ingenious ideas into reality at Intuit. Discover what it's like to be part of a team that rewards taking risks and trying new things. It's time to love what you do! Check out all of our career opportunities at: careers.intuit.com. EOE AA M/F/Vet/Disability Intuit will consider for employment qualified applicants with criminal histories in a manner consistent with requirements of local law.

The Senior Analyst will help define key performance indicators and implement a testing and reporting framework to provide actionable insights to Marketing and Product about our ESPN+ and Disney+ subscriber, and drivers of retention and engagement. This position will work closely with Data Science and Research to develop, track and analyze A/B and multivariate experiments for our retention initiatives. Responsibilities: Use exploratory analysis to deeply understand customers and their behavior across platforms. Work with the Marketing team to formulate quantitative and measurable objectives that have an impact on the business. Partner with Marketing, Data Science and Research on the end-to-end process of test design, implementation and analysis. Use statistical and inferential methods to deepen our understanding of patterns and trends in user behavior and uncover new opportunities. Create applied advanced analytic solutions/predictive modeling to understand and drive retention and to optimize LTV of audience segments. Help build a data driven culture where testing is a key part of the workflow. Create a documentation process for all tests, communicate with other areas of the organization running tests, and document and communicate findings and insights to stakeholders across the company, including senior executives. Basic Qualifications: 3+ years of experience in an analytical role, which include 2 years of work experience using SQL and knowledge of Python/R or other statistical programming language. Understanding of statistics concepts (e.g., hypothesis testing, regression analysis) and experience in applying multivariate statistics, including logistic regression modeling, to business problems. Experience with defining, implementing and analyzing A/B and multivariate experiments. Strong communication and presentation skills – written, visual, and verbal presentations. Required Education: Degree in an analytical field such as economics, mathematics, statistics, physics, engineering, or computer science. Preferred Education: Advanced degree is a plus.