Irvine, CA 92618
Location: Irvine, CA
Salary: $90,000 - 110,000
Contact: Paul Chatlos, [email protected]
Data Scientist Responsibilities
-Collect data from a wide variety of corporate databases and Excel files.
-Utilize your toolset in regular expressions to extract information from un-structured text documents and the web.
-Handle missing data through an algorithmic approach such as multiple imputations to enable insights in sparse and messy data.
-Use your inner whiz-kid to feature engineer the data to boost model accuracy.
Data Scientist Predictive Modeling
-Utilizing your algorithmic/programming toolkit, build predictive models to drive acquisition, engagement and retention and improve growth and profitability, and other such key performance indicators for our business.
-More specifically, apply algorithms equal or similar to the following: elastic net regularization for regression, random forests, generalized boosted models, generalized additive models, support vector machines, neural networks, and time-series forecasting. Ability to communicate implications of the level of confidence in each of the models.
-Implement formal modeling processes from end to end including data gathering, data profiling, numerical model building, calibration, cross-validation, putting product into production, etc.
-After building the models, pilot "scorecards" to track model performance and calculated improvement to business.
-Explain complex modeling approaches in layman's terms and discuss modeling results and business case impacts with non-technical business users.
Data Scientist Test/Learn Analytics
-Develop a portfolio of test and learn programs, lead the test design and measurements/goals and manage the day-to-day execution of the corresponding analyses.
-Establish robust A/B and fractional factorial testing methodologies including sample size requirements for readability and go/no-go criteria for scaling.
-Lean-out testing processes to cut end-to-end cycles times and accelerate weekly test cadence.
-Manage testing calendar and minimize test collisions given test objectives and audiences.
-Establish tracking of value identified, validated in-market, and scaled across marketing channels and eCommerce.
-Create, maintain, and deliver dashboards and reports for KPI results from test measurements and communicate results to key stakeholders.
-Monitor and interpret results and suggest next steps for new test and rollout of programs to key stakeholders.
-Conduct ad hoc analysis for internal partners as requested, including in-depth funnel and conversion analysis
-Support the maintenance and development of web analytics platforms.
Data Scientist Customer Glidepath and Audience Management
-Develop and maintain comprehensive customer segmentation models and recommendations for key focus segments.
-Identify targeted audiences to optimize marketing communications for digital media, on-site personalization, and one-to-one marketing (e.g., email, SMS, and direct mail) leveraging transactional data, online-browse behaviors, and 3rd parties.
-Develop thought leadership on best variables and fields to define key audiences for customer glidepath management efforts.
-Partner with IT to build, manage, and refresh audiences in relational databases and campaign management platforms to execute segmented marketing programs.
-Lead deep dives to identify highest performing audiences in digital media, on-site personalization, retargeting, and one-to-one marketing campaigns.
-Develop audience targeting plans for media buying, on-site personalization, and one to one vehicles.
-Collaborate with vendors to build audiences in external databases and systems (e.g., DMP, third-party demographic data, etc.).
-Execute ad-hoc analyses as requested by leadership for development of segmented contact strategies.
-Create and main
Data Scientist Mixed Media Modeling Emphasis