#LI-Post

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  Responsibilities:

• Independently develop and deliver data science projects/modules with medium to high complexity
• Identify machine learning algorithms and methods best suited to solve specific business problem
• Build robust code in Python, R etc. in data science projects
• Understand business problem and provide solution using data science and analytics
• Network with the organization to obtain required data from multiple sources
• Data management for data science projects – Data extraction, validation, cleaning, processing and storage
• Effectively communicate with clients
• Transform data science prototypes into machine learning systems.
• Build cost effective and efficient systems using parallel processing and other methods.

  
  Experience Required:

• Experienced in building multiple data science projects of medium to high complexity
• Deep knowledge of math, probability, statistics and algorithms.
• Experienced in writing robust codes in Python, R etc.
• Understanding of data structures, data modelling and software architecture.
• Exposure to complete life cycle of data science projects
• Experience in implementation of data science projects
• Exposure to ML platforms like Databricks etc.
• Experience/Exposure to Big Data technologies like Spark/Scala.
• Worked directly with clients and stakeholders.
• Experience 10 plus years in data science & Machine learning projects

  
  Education:

• Master Degree or higher in one or more of the following quantitative disciplines, i.e. Mathematics, Statistics, Economics, Computing.

About the team:

We are the global Finance analytics team, located primarily in Houston, TX and Bangalore, India. We design, develop and deploy production solutions to facilitate various Finance, Accounting, Planning, and Business Operations inside of HP. Our team has a mixture of disciplines ranging from Statisticians, Economists, Finance, Engineers, Front-end, Back-end, and visualization developers. HP is currently going through enterprise-scale transformation initiatives that heavily relies upon a data-driven culture. Our current focus for the coming year will be heavily forecast-related. Our team is flexible, dynamic, hungry, and humble; we are excited to find like-minded individuals!