Identify, develop, implement and drive adoption of analytics-based solutions to business problems in XPO
Lead and mentor other data scientists, and build a highly functional and motivated team
Serve as a subject matter expert in the organization on data science, providing scientific support across the company and for end customers
Carry out descriptive, predictive, prescriptive analytics and communicate findings to leadership and stakeholders
Design the AI Roadmap for the global organization and conceptualize AI initiatives to do R&D on
What you need to succeed at XPO:
At a minimum, you’ll need:
Bachelor’s degree or equivalent related work in Engineering, Computer Science or a related technical field
12+ years of experience delivering data science solutions in production and doing R&D
Experience of scoping, planning, development, deployment, and tracking of data science solutions
In-depth understanding of statistical modeling, data analytics, model building and visualization using expert level understanding of Python (Numpy, Pandas, Scipy, Plotly and Matplotlib) and its object-oriented programming concepts
Expert in writing SQL fluently, recognizing and correcting inefficient or error-prone SQL and performing test-driven validation of SQL queries and their results
Some exposure to ML Platforms such as Google Cloud, AWS or Azure and experience of putting multiple data science models into ML pipelines in production
Basic understanding of LLM fundamentals and how to best use Generative AI for solving problems
Exposure to visualization tools such as Looker Studio, PowerBI or Tableau
Strong programing and algorithm development skills as applied to working with large data sets
Attention to detail and motivation to minimize error
Experience with data modeling and data architecture
Ability to mentor, teach, and motivate junior team members and extract their maximum potential
It’d be great if you also have:
Master's degree in data science, Computer Science, MIS, Engineering, Business or a related field
In-depth understanding of developing and deploying production grade data science solutions
Exposure to wide array Google Cloud Products such as BigQuery, Vertex AI, Cloud Functions, Cloud Run, Pub/Sub Trigger etc
Exposure to LLM fundamentals and understanding of Langchain, RAG architecture and using various large language models to develop a solution by using it as API wrapper or by custom training
Multiple data science specialization courses done from Coursera, Udacity, Data Camp, etc.
