Marketing Data Scientist/Data Engineer
256 West 36 Street Fl 11 New York, NY 10018
Title: Marketing Data Scientist/Data Engineer
Location: New York, NY
Company: Thriving plus size start-up
MUST have retail eCommerce experience and interested in working for a successful start-up
As a Marketing Data Scientist/Data Engineer you enjoy working with large sets of data, transforming them, and solving complex problems. In this role you will help drive growth of the business through fact-based insights, data-driven analysis and optimization of the ecommerce experience. With your strong analytic skills and a commitment to quality analysis, you will be a key member of the team where you will use a variety of tools and methodologies to turn raw data into customer insights and provide recommendations to improve the business.
Among other things, this role is responsible for developing, maintaining, and optimizing customer-data-based modeling (customer segmentation, inventory patterns, customer lifetime value, recommender, multi-touch attribution models). You will also develop analytical models to drive prospect and customer audiences for acquisition customer glidepaths, and tailored contact strategies. In addition, you will be tasked with defining and tracking metrics of success across the business, building predictive data products, and supporting the analytical needs of teams throughout the company.
- Develop and implement data warehouse, infrastructure and and analytics platform to effectively capture, transform, integrate, organize, maintain and use data.
- Build state-of-the-art data analytics and reporting solutions to report on performance metrics, site engagement, conversion, marketing campaigns, financial reporting, web analytics, segmentation, customer journey, etc
- Develop both short-term and long-term strategy for architecting how data is captured, stored, and leveraged in order to create a first-class data-driven organization
- Built out the monitoring framework, and own the full pipeline from ideation, design, implementation, to impact analysis
- Build custom models to understand customer behavior, marketing analytics, inventory patterns, etc.
- Capture e-commerce KPIs and analyze trends over time.
- Perform deep dive analysis into specific KPIs to understand the underlying influences. Manage the team dashboard that crosses all functions.
- Design and analyze rigorous experiments aimed at understanding customer behavior.
- Extract insightful information from messy and unstructured data in order to drive strategic decisions at the company.
- Perform analysis and submit recommendations to improve return and revenue.
- Improve website functionality and conversions while understanding and maintaining brand positioning.
- Responsible for tracking, reporting and analysis of homepage, landing page and creative tests as well as the shopping funnel to optimize online marketing and site merchandising efforts.
- Research and provide competitive insight to the team in organized reports.
- Manage projects from concept to completion, monitoring the status and facilitating timely communications.
- Utilizing your algorithmic/programming toolkit, build predictive models to improve profitability, growth, retention and other such key performance indicators.
- 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
- Maintain and optimize customer models, including identification of key behavioral and attitudinal variables to drive marketing effectiveness.
- Partner with marketing team to identify targeted audiences 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.
- Develop and maintain multi-touch attribution models across digital channels (e.g., paid search, display, affiliate, paid search, etc.)
- Lead deep dives to identify highest performing segments and audiences in digital media, on-site personalization, retargeting, and one-to-one marketing campaigns.
- Create and maintain reports detailing performance of key segments and audiences and communicate results to key stakeholders.
- Bachelor' s degree required in Business, Economics/Finance, Engineering, Statistics, Computer Science or related field. Masters a plus.
- 5+ years previous work experience (retail / e-commerce experience) with strong understanding and proficiency of predictive modeling and advanced analytics
- Experience setting up and developing data infrastructure from the ground up
- Proficiency in SQL, Microsoft Office Suite and at least one of the following: R, and/or Python.
- Advanced Excel experience required.
- Shopify experience is a plus
- Superior research, statistical, analytical, processing and mathematical skills with ability to structure and conduct analyses.
- Must be a hands-on team member and operate with a start-up mentality.
- Technical knowledge including html, tag management, basic front end code.
- Organized, detail oriented and the ability to transform concepts into actionable plans.
- A love of all things data.