Data Scientist

Posted:
8/28/2024, 2:34:36 AM

Location(s):
Tampa, Florida, United States ⋅ Illinois, United States ⋅ Indianapolis, Indiana, United States ⋅ Charlotte, North Carolina, United States ⋅ Arizona, United States ⋅ Tempe, Arizona, United States ⋅ Chicago, Illinois, United States ⋅ Indiana, United States ⋅ North Carolina, United States ⋅ Florida, United States

Experience Level(s):
Senior

Field(s):
AI & Machine Learning ⋅ Data & Analytics

Today’s logistics marketplace is an ever-changing landscape where you can make your mark. Spot gives you the tools to tackle industry challenges for our partners. Here, initiative, drive, and teamwork form the basis for a rewarding, fast-paced career.

About the Role:
We are seeking a talented Data Scientist with a passion for solving business problems through the creation and management of dynamic pricing models. In this role, you will lead the innovation and support of our dynamic pricing engine, directly impacting Spot's growth, profitability, and overall efficiency. You will manage a team of data scientists to navigate the complexities of dynamic pricing in a constantly changing market, using our rich database of millions of data points to build and maintain effective pricing strategies. Our system is used by hundreds of internal users, handling over 100k+ requests a month, and driving millions in monthly revenue.

Key Responsibilities:

  • Collaborate with a team to innovate and continuously improve Spot’s dynamic pricing engine by integrating new data sources and model enhancements to optimize pricing strategies.
  • Apply data science techniques including machine learning, AI, and statistical modeling across multiple functional areas of the organization to drive improved decision making
  • Serve as a highly qualified technical resource to Spot’s senior management team, with heavy involvement in driving continued growth & scaling of the organization
  • Create and track accuracy and performance metrics (both technical and business metrics) of models & tools
  • Create, enhance, and maintain technical documentation, and present to scientists, engineers, and business leaders

Basic Qualifications:

  • 5+ years of experience with data scripting languages (e.g., SQL, Python, R etc.,)
  • 1+ years of transportation and logistics experience is preferred
  • At least 3 years of experience in quantitative analytics or data modeling
  • Deep understanding of predictive modeling, machine learning, clustering and classification techniques, and algorithms
  • Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark)

Additional Information:

  • Visa sponsorship is not available for this position.
  • This position is available at our Indianapolis, Tampa, or Chicago office locations only.

#LI-CH1 

Spot is built on relationships, combining 24/7 support with a proven, passionate, and dedicated team of logistics professionals. You can reach your true potential through the unlimited opportunities we offer. When you put in the effort, show initiative, solve problems, and build lasting client relationships, you earn respect and rewards. You’ll also be a key component to the success of an industry leader. At Spot, we’ve never lost the entrepreneurial spirit that provides the foundation for our success.

Spot Freight, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Spot Freight is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a disability, you need a reasonable accommodation, please contact our Human Resources team to notify us of your request. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.