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Form of workOverview
IXIS is seeking an energetic and innovative quantitative researcher with fluency in statistics and machine learning, experience with digital/marketing methodologies and a proven ability to execute analytic initiatives to fill the company's Data Scientist position. This is a full-time, remote or hybrid position in our Burlington, Vermont or Washington, DC area office. We offer competitive compensation packages including health, dental, life, short-term and long-term disability and vision insurance, 401(k) with company match, flexible work schedules, and exceptional growth opportunities.
The core responsibilities for this role include working with a team to design sophisticated quantitative solutions-frequently through integration of novel data sources-and executing these solutions programmatically and reproducibly. The ideal candidate will combine deep technical expertise in programmatic statistical analysis and predictive modeling with strong data IQ to create data-driven visuals and narratives that answer client questions.
Responsibilities
- Design and execute quantitative analyses to extract actionable insights that directly address client needs and questions
- Import, clean, integrate, explore, and visualize large datasets to support ongoing research projects and ad hoc client requests
- Use R and other software tools (SQL, GitLab) to ensure that quantitative analyses are reproducible, and leverage CICD pipelines to deploy automated jobs in our AWS stack
- Work with data engineers to plan, implement, and automate integration of external data sources across a variety of architectures, including local databases, web APIs, CRM systems, etc.
- Work with our quantitative and development teams to design and implement automated data analysis and predictive modeling technologies in support of client deliverables
- Participate in quantitative requirements meetings to build supporting evidence for retail and digital strategies
- Collaborate with technical, development, database and QA engineers
- Prioritize multiple tasks intelligently and maintain clear lines of communication with supervisor, team, and clients
Desired Skills and Experience
- B.A./B.S. in Computer Science; or B.A./B.S. in a quantitative area (such as Statistics, Mathematics, Data Science or Economics) with a minor (or equivalent experience) in Computer Science; post-graduate degree preferred
- 2+ years' professional experience with programmatic data analysis (R / Python); experience with R and tidyverse packages (dplyr, purrr, ggplot, Shiny) preferred
- Experience working with real-world datasets, including database queries, data aggregation, record linkage, data cleaning/reshaping/management, and descriptive data analysis; data visualization and automated reporting experience preferred
- Experience with MMM (Media Mix Modeling) and CLV (Customer Lifetime Value) modeling to develop data-driven insights
- Excellent attention to detail, critical thinking skills, and a systematic approach to problem-solving, with strong data intuition
- Experience with the following is a plus:
- Exposure to digital analytics (such as Google Analytics or Adobe Analytics) and e-commerce fundamentals
- Developing data science solutions within a cloud environment (ideally AWS)
