Lead Data Scientist

Visa: Open


Interview: 2-3 rounds of video interviews

LinkedIn profile is mandatory.

Job Description:


Job Title: Lead Data Scientist


Location: 100% REMOTE


Duration: 3 months contract to hire.


Interview Process: 2-3 rounds of video interview

CPG and Retail Industry experience is highly preferred.

Client is a leading digital innovation partner for the world's most ambitious brands. Our organization creates transformative digital experiences through services that include strategy, experience design, technology, analytics and insight, and marketing.

We are looking for an experienced Data Scientist with a background in marketing analytics, ideally with CPG or retail industry experience. This role will create recommendations, personalization and segmentation for marketing purposes, and solve other interesting challenges within data science applications in marketing channels and campaigns. The ideal candidate would be highly adaptable to new areas of domain knowledge and have a natural curiosity for what patterns and pain points connect the business world. This candidate would have the ability to develop various types of models from ideation to deployment while maintaining a focus on activation and client goals.

The Data Scientist will collaborate closely with a Data Strategy Consultant on working with clients to explore business objectives for analysis and model creation. This role will be focused on partnering with a client serving CPG and Retail brands to identify insights to optimize various marketing strategies. This role will have access to large amounts of high quality consumer data from top companies in the CPG and Retail space.

Role and Responsibilities:

• Use critical thinking and creative problem solving skills, leveraging digital marketing expertise to translate high-level business objectives into short and long term solutions around audience segmentation, multi-touch attribution, and journey orchestration
• Produce model-driven solutions in various platforms for a wide range of business problems and industries using best-practice techniques in regression and classification while demonstrating a connection to marketing strategy principles
• Collaborate with internal marketing, design and strategy teams to define and execute cross-functional solutions, driving meaningful activation in digital marketing platforms with measurable impact for clients
• Work closely with clients to identify and elevate opportunities for data-driven solutions improving digital maturity in audience targeting and personalization.
• Articulate complex ideas in a clear and concise manner, both in speech and writing; understand the audience and tailor messages accordingly
• Aggregate and analyze disparate datasets, including web analytics, customer, and marketing data to draw conclusions and deliver actionable insight
• Pragmatically decide between developing custom modeling frameworks vs implementing out-of-the-box solutions dependent on business needs
• Contribute to a highly collaborative data science team with brainstorming, peer reviews, and knowledge transfer to increase consistency of deliverables and repeatability of solutions
• Follow developments in the field by continuous learning and proactively champion promising new methods relevant to the problems at hand

Qualifications:

• Bachelor's degree demonstrating skills in quantitative and scientific methods such as math, statistics, natural sciences, finance, social sciences; advanced degrees a plus; additional education in data science-specific fields, certifications and degrees a plus
• 7+ years of experience in digital marketing consulting and analytics, with 3+ years applying machine learning algorithms for clients
• Extensive experience building machine learning solutions in a cloud stack (GCP, AWS, or Azure)
• Depth of knowledge in digital marketing data including datasets from channels such as paid media and web analytics
• Demonstrates advanced SQL skills (partitioning, nesting, regex, etc.)
• Demonstrates high level of proficiency in Python , and at least one data science toolkit (Sklearn, Tensorflow, etc.)
• Some experience with data visualization
• Some experience with productionizing a ML system, e.g. exposing via API, creating service layer, etc.