Digital Marketing Data Scientist

You will be a team member of the Digital Marketing Analytics team, working in the data sciences area, with specific focus on Digital Marketing business problems.

You’ll be responsible for supporting analytics that drive business optimizations across the customer end-to-end journey. This role will support the full cycle of an experiment (from data-driven hypothesis generation to test design to analysis and interpretation) while also innovating on experimental methodologies that allow us to obtain meaningful results.

You should have hands-on technical experience in statistics, predictive modeling and other data sciences, as well as extensive experience in developing data-sets for data science projects. The position requires superb communication and advanced analytical skills.

• Total Indicative Experience: 4-7 Years (or equivalent education) with experience in Digital Marketing specifically.

• Hands-on experience with one or more of the primary data science tool-sets: R, SAS, SPSS, Python, and models such as ARIMA.

• Hands-on experience with Adobe Analytics, Tableau and/or Power BI.

• Experience using advanced analytics techniques to tackle digital marketing business problems, such as, pre-funnel behavior analysis to predict insights in the digital journey prior to web form conversions, insights across tactics, multi-touch attribution, campaign sequencing, ROI analysis for paid campaign efficacy, and forecasting for pipeline metrics.

• Working knowledge of methods such as regression, cohort analysis, hypothesis testing, cluster analysis with hands-on experience translating raw data from relational databases and Hadoop into modeling data sets (using Excel, SQL, SAS or other coding tools) is desired.

• Good business & technical communication skills, both verbal and written. Ability to explain and present analytics concepts to non-technical audiences. Ability to establish & cultivate relationships with all stakeholders.

• Proven project management and organizational skills. Ability to effectively prioritize time, manage expectations and deliverables. A self-starter, who proactively looks for new and better ways of doing things. Shows drive, passion and a sense of ownership.

• Graduate degree in data sciences, advanced analytics, statistics or related fields is preferred, or equivalent on-the-job experience (experience in high-tech enterprise business-to-business industry is ideal, as is prior experience from a reputed analytics firm doing similar work).

All your information will be kept confidential according to EEO guidelines.