The problems we solve everyday are real and require creativity, grit, and determination. We are building a culture that challenges norms while fostering experimentation and personal growth. We're hiring team members who are passionate and are energized by the vision to simplify and transform one of the largest and most complex industries through technology, data and a strong commitment to customers.As our Director, Data Science you will lead a team of talented Data Scientists and Analysts to build and evolve the core engine of Transfix’s marketplace. Using traditional and non-traditional techniques, you will lead the creation of pricing models, market forecasts, auction bidding strategies, and carrier matching algorithms. You will work with a varied set of teams across the organization to drive our company’s most important business goals.If you’re excited about transforming an industry, being part of an innovative culture, and making a positive impact on the environment, send us your resume.
What's you'll do
- Set strategy and roadmaps for our Data Science and BI teams
- Develop models to predict freight costs and market forecasts using time series modeling and forecasting
- Create bidding and pricing strategies for automated daily and annual auctions
- Deliver carrier-network matching algorithms and advanced network analyses to unearth optimization opportunities
- Collaborate with our Sales, Account Management, and Operations teams to drive company KPIs.
- Drive adoption of improved processes and innovative technologies and tools
- Promote a culture of data-driven decision making by evangelizing and making data and insights easily accessible across the organization
- Partner with data engineering for system design and infrastructure
- 3+ years experience leading and managing high performance Data Science teams
- 5+ years experience performing statistical modeling, machine learning, and advanced analytics with structured and unstructured data.
- Strong problem solver who is comfortable devising creative solutions when presented with imperfect or sparse data sets
- Experience with two-sided marketplaces and supply-demand dynamics
- Biased for action and driving impact rather than “perfect” theoretical solutions
- Experience in bidding and pricing (e.g., quant experience)
- Deep experience with SQL and Python or R
- Proficiency in math, statistics, economics, engineering, or a related field.