Lead Data Scientist

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

As a Lead Data Scientist, you will be responsible for rapidly delivering analytical solutions to functional areas of the business such as Manufacturing, Sales, Marketing, etc. Through Microsoft Azure, you will help deliver insights to both Product Owners and Product Users. You will collaborate with fellow Data Scientists and others to execute and deliver working solutions to end users. Working as a collaborative member of thehive team, you will use data science and machine learning techniques to help drive deep data analysis and uncover insights that will enable the business to make strong and strategic decisions.

PRIMARY RESPONSIBILITIES:

• Utilizes analytical, statistical, and programming skills to understand how possible analytical techniques align to business questions and challenges across the Purina enterprise
• Models statistical and analytical solutions to business challenges using diagnostic, prescriptive and predictive techniques by collecting, analyzing, and interpreting large data sets
• Work with functional business partners to fully understand their data and enable insight discovery
• Visualize and communicate insights using visualization tools such as Power BI
• Embeds successful value generating models as key components in industrialized solutions within operations through collaboration with Solution Architects or Data Engineers
• Supports analytical maturity through evangelizing and providing insights to key business and internal stakeholders and is viewed as a coach by other data scientists
• Knows how to calculate real and estimated business value return for various analytical use cases
• Participate in the end-to-end lifecycle of analytics and data projects through the use of DevOps, code and model management, CI/CD and other industry standard practices that enable analytics at scale

REQUIRED QUALIFICATIONS:

• Bachelor’s Degree or higher in Data Science, Computer Science, or related field 
• 5+ years of professional experience in data analysis
• 2+ years professional experience in a data science role
• Advanced proficiency in Python or PySpark and use of relevant libraries (such as MLlib) previously delivering business value 
• Professional experience in building, training, and testing AI/ ML models based on the data
• Professional experience in creating visualizations and using tools to present/tell the story of the results (PowerBI or Tableau)
• Experience with internal or external customer-facing consultation

PREFERRED QUALIFICATIONS:

• Experience with AZURE or similar cloud platform
• Experience with query languages such as SQL, MDX, and DAX
• Basic understanding of Agile and CI/CD DevOps principles
• Professional experience in productionizing and scaling successful AI/ML models with proven value return
• Experience with formal or informal mentoring/coaching programs