This is a full-time hybrid position in our Burlington, Vermont or Washington, DC area office.

IXIS is seeking an experienced data analytics practitioner with demonstrated technical and organizational leadership in the field of marketing and digital analytics to fill the position of Director, Strategic Analytics for the company. The core responsibilities for this role will be to apply and innovate quantitative methodologies that provide actionable insights into our clients’ customer journeys, including predictive customer lifetime value, churn modeling, segmentation and profiling, media attribution, and incrementality estimation. You will be asked to lead and grow a highly efficient and strategic data science team within an organization experiencing rapid growth and transformation. You will be encouraged to develop solutions that can be scaled within our proprietary ATLAS data platform, and you will have the opportunity to contribute directly to our product roadmap by productizing innovations developed during client engagements. The ideal candidate will have multiple years of experience performing advanced customer analytics for top-tier businesses in omnichannel retail, CPG, automotive, or similar verticals.

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.

Responsibilities

• Lead, manage and grow a client-facing data science team with a particular focusing on finding and developing talent who can succeed in a complex organization
• Work closely with Account Strategy teams to ensure that analysis is thorough, accurate  and actionable
• Maintain the overall analytics strategy to align with business and strategic objectives set out by client and client strategy teams
• Plan, design and implement quantitative solutions for our B2C clients that drive actionable and ongoing insights, leveraging state of the art ML/AI technologies and libraries to solve real-world business problems
• Provide technical leadership for advanced customer analytics initiatives, including predictive customer lifetime value, churn modeling, segmentation and profiling, media attribution, and incrementality estimation
• Lead requirements gathering for advanced data science projects, oversee technical/design documentation, and communicate progress and results to non-technical audiences
• Organize and oversee the progress of technical project teams, including other data scientists, data/ML engineers, and data analysts, as required to deliver larger quantitative solutions
• Identify and prioritize opportunities for new data science products and ML/AI applications as offerings for our clients and/or as features within our ATLAS data platform
• Use Python/R and a modern data science stack (dbt, AWS, Docker, Gitlab) to ensure that solutions are reproducible, extensible, and easily integrated into the ATLAS data platform
• Lead by example: Foster a culture of curiosity, creativity, experimentation, and continual improvement among the data science team
• Work with data/ML engineers and back-end engineers to deploy and maintain predictive models in an AWS production environment
• Collaborate effectively across teams and departments, including strategists, account management, engineers, product, and design/UX
• Prioritize multiple tasks intelligently and maintain clear lines of communication with supervisor and team

Minimum Requirements

• B.A./B.S. in a quantitative field (such as Statistics, Applied Math, Data Science or Economics); post-graduate degree preferred (commensurate professional experience will be considered)
• 5-7 years’ professional experience with programmatic data analysis, visualization, and modeling using Python/R + SQL; must be adept at functional programming and love writing clean code – exposure to DevOps and MLOps practices a plus
• Professional experience with A/B testing, ideally in an ecommerce context, including design and analysis of controlled experiments
• Expertise working with data in the wild, including structured and unstructured data, record linkage/householding, data munging/reshaping, descriptive and inferential statistics, and data visualization for exploratory and presentation purposes
• Demonstrated success developing and deploying ML pipelines for business applications
• Automotive and/or retail eCommerce experience a plus
• Fluency with marketing fundamentals (up to and including MMM) and digital analytics (Google/Adobe Analytics) a big plus
• Uncompromising attention to detail, critical thinking skills, and a systematic approach to problem-solving, with strong data intuition