Director of Data Science

Collaborate with cross-functional partners in operations, finance, marketing, and engineering to understand business imperatives and scope data science projects; Explore possibilities to solve the business imperatives by identifying data sources, creating data where needed, and applying data science techniques; Work with VP Data, VP of Analytics, and CFO to create data-informed business strategies and roadmaps; Translate data needs into data product requirements, evaluate technologies, and identify opportunities to innovate and improve data science capabilities; Use creative problem-solving skills to analyze data and build statistical / machine learning models to help solve business problems from different perspectives; Work with data engineering lead to create services that can ingest and supply data to and from both internal and external sources and ensure data quality and timeliness; Build the data science team and lead in data scientist recruitment process; Guide and coach data scientists and own the deliverables of data visualization and dashboards to help the organization monitor performance, generate insights, and continuously improve user experience; Continuously grow the data science team's skillsets; Establish playbooks to drive data product development process and consistent outcomes; Use strong communication skills (written and verbal) to lead the full lifecycle of model development, which spans from business problem discovery, data discovery to model deployment and monitoring; Evangelize data science across the entire company; identify and make the business case for data science based use cases; Where needed, conduct hands-on wrangling, processing, cleansing, and verifying data from different sources used for analysis; Analyze data with complex relationships, hierarchical levels, and time series, such as Pandas, PySpark; Use and recommend a wide range of machine learning algorithms and statistical modeling, including latest LLM developments; Utilize data visualization and dashboard tools, such as Tableau, PowerBI and Snowflake. Up to 10% domestic travel required for meetings/clients visits; 100% remote; must reside in U.S.; reports to HQ in New York, NY. Salary: $336,350 - $356,350 per year., Must also have experience in the following: 5 years of professional experience implementing data science solutions by identifying relevant data sources, creating data pipelines, and applying advanced data science techniques to support business decision-making; 5 years of professional experience designing and developing machine learning models and statistical algorithms to analyze structured and unstructured data from both internal and external sources; 5 years of professional experience collaborating with cross-functional teams to gather business requirements, define technical scopes, and deliver actionable data insights; 5 years of professional experience utilizing tools and libraries including Python, SQL, Spark, PyTorch, Pandas, and PySpark to perform data wrangling, cleansing, and advanced analytics; 5 years of professional experience developing and maintaining data visualization dashboards using tools including Tableau to monitor performance and, communicate insights to

MINIMUM REQUIREMENTS: Bachelor's Degree or U.S. equivalent in Quantitative Methods, Statistics, Econometrics, or related field, plus 5 years of professional experience as a Data Scientist, Operations Research Analyst, or any occupation, job title, or position leading a data science team in a technology organization., stakeholders, 5 years of professional experience establishing scalable data product development processes through consistent use of playbooks, code standards, and reproducible pipelines; 5 years of professional experience leading the full lifecycle of machine learning models from business problem discovery to model deployment and performance monitoring; 5 years of professional experience evangelizing data science practices across organizations, including coaching team members, supporting recruitment efforts, and promoting a data driven culture.