About Sabio and App Science:
Sabio, the CTV platform powered by mobile data, provides leading brands with the perfect balance between media, data, and technology. Sabio’s unique approach to combining mobile data, device location, and consumer behaviors provides brands with more effective targeting and greater prediction accuracy for their mobile and connected TV ad campaigns. Sabio was founded in 2014 by veterans in the mobile and TV industries and is headquartered in Los Angeles.
App Science® is a subsidery of Sabio, Inc. and is our data, AI, and insights platform. AppScience models and build unique audiences, maintains an industry leading household graph, and measures CTV/OTT performance & provides actionable insights in one easy-to-use platform. Leading brands and agencies use App Science to activate, measure, analyze, and improve their campaigns with proprietary insights.
Job Description:
App Science is looking for a Data Science intern to join our team. Our Data team is responsible for aggregating millions of consumer data points to best-in-class AI predictive models, consumer trends systems, AI recommendation engines and more. The candidate must have a proven track record of developing business model solutions and extracting meaningful business insights from big data.
Duties & Responsibilities:
- Execute the data vision strategy and goals ensuring those are consistent with the Division’s business requirements.
- Help develop analytical capabilities, data products and tools to enable data query and deliver solutions to business requests
- Generate actionable audience insights using advanced AI and statistical techniques such as predictive statistical models, audience profiling, segmentation analysis, survey and test design, exploratory analysis and data mining.
- Understand in depth, design and inform statistical testing for audience strategy
- Design user interfaces to overlay AI and ML models, and enable business partners to access models, query results and scenarios.
- Build presentations and reports to communicate statistical modeling results
- Find creative ways to use data for strategic advantage and further company objectives
- Recommend improvements in data science procedures and processes
- Partner with business departments to highlight the most impactful data science findings
- Review analysis validation data to ensure results are accurate, valid, and reliable
- Suggest innovative ideas to increase productivity and improve overall impact and experience
- Profile, explore, connect and analyze extensive, often disjointed, and unstructured datasets including product meta data, user level data, primary research, audience profiles, social commentary and DMP data.
Requirements:
- Seniors and graduate students preferred; must be enrolled in an undergraduate or graduate program, or be a recent graduate in Mathematics, Computer Science, Physics or related
- Interested in a career in the Digital Media and AdTech industry
- Must have an in-depth knowledge of advanced statistical techniques, machine learning, feature engineering, and model evaluation techniques including regressions, cluster analysis test design, variable reduction, non-parametric tests and forecasting methodologies.
- Ability to work with data and platform engineers to implement ML pipelines
- Experience with R and SQL and preferably a scripting language (Perl, Python)
- Business experience in media industry preferred, but not required
- Results oriented, excel in organizational skills, have strong attention to details and be able to effectively manage multiple projects/assignments simultaneously.
- Curious about data and problem solving: intrinsic ability to look at data and identify patterns, problems, or analysis opportunities
- Strong communication skills and the ability to explain complex analyses to both technical and non-technical audiences
- Effective data visualization skills with analytical tools such as Tableau, Shiny, DASH, Periscope
- Collaborative – a team player who can thrive as an individual but also enjoys learning new approaches, and being collaborative in cross-functional teams
Sabio is an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Sabio is an equal opportunity employer and values diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
PRIVACY NOTICE TO SABIO’S JOB APPLICANTS
This Privacy Notice explains what personal information we at Sabio, Inc. collect from you, and why we collect it and use it. This Notice covers our practices regarding the personal information of all applicants to our job positions. Please review it carefully.
Categories of personal information we collect from you
Generally, We Obtain This Information Through Our Recruiting Team
We collect personal information about you throughout the recruiting process, in particular the following categories.
- Identification and contact information
- Direct identifiers such as your first and last name.
- Indirect identifiers such as a government ID, your Social Security, work permit or passport #.
- Contact information such as your email address, mailing address, telephone number.
- Other information about you or that can be associated with you such as:
- Sensitive/Protected Data. During the recruitment process, you may (voluntarily) provide us with your ethnicity, gender, military service information, or physical or mental health information, as well as your national origin and citizenship.
- Professional or job position-related information , including your past professional experience, references; background verification; talent management and assessment; information regarding any conflicts of interests; and the terms and conditions of your job offer.
- Non-public education information , including information about your education records, such as grades and transcripts.
