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Intern Data Scientist

  • Anywhere

Company :
Adobe

Location :
Seattle, Washington

Expiry Date :
Sat, 05 Dec 2020 23:59:59 GMT

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Description :
Our Company Changing the world through digital experiences is what Adobe’s all about. We give everyonefrom emerging artists to global brandseverything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! The Opportunity The Digital Imaging team (Photoshop, Lightroom, etc.) is looking for a Data Science Analyst who is passionate about data and is driven to give customers the best experience possible. Tapping into our extensive product usage data sets, you will work directly with product managers, researchers, and engineering teams to harness our data, derive meaningful insights, and help lay the foundation for robust and reliable data-centric decision-making. You will have the opportunity to exercise creativity in problem solving by delivering inventive new solutions within our data ecosystem. We invite you to join a team of hardworking data professionals to elevate our customer experiences to the next level. Come make impact on two of the most exciting and important products at the company! What You’ll Do – Construct machine learning pipelines to map customers to persona-based segments based on in-app usage data – Build models to recommend personalized in-app learning content – Analyze usage patterns to better understand customer behavior including acquisition, engagement, conversion, and retention – Identify customer trends and communicate relevant insights to assist product decision-making – Drive A/B/n tests and design of feature-level experiments to validate hypotheses and drive product development decisions – Work with engineers to understand existing product instrumentation and help bridge gaps in data streams to assist data science programs – Automate data pipelines using SQL or Python based ETL Frameworks What You Need To Succeed – MS degree in an analytical field: statistics, applied mathematics, computer science, engineering, economics, etc. – Experience translating business questions into data analytics approaches – Strong proficiency in querying and manipulating large datasets using SQL-like languages (Hive, Spark, etc.) – Experience building machine learning algorithms and pipelines using Python or R – Experience crafting and analyzing experiments, using appropriate statistical techniques to mitigate bias and interpret statistical significance – Familiarity with descriptive and inferential statistics (e.g. t-test, chi-square, ANOVA, correlation, regression, etc.) to understand usage behaviors and generate hypotheses – Experience creating data visualizations and storytelling to effectively communicate analysis results to both technical and non-technical audiences – Knowledge of relevant tools in this field such as Hive, Tableau, Excel (Charting and PivotTables), and PowerBI At Adobe, you will be immersed in an exceptional work environment that is recognized throughout the world on Best Companies lists. You will also be surrounded by colleagues who are committed to helping each other grow through our unique Check-In approach where ongoing feedback flows freely. If you’re looking to make an impact, Adobe’s the place for you. Discover what our employees are saying about their career experiences on the Adobe Life blog and explore the meaningful benefits we offer. Adobe is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, or veteran status.