Data Scientist II - Gas System Integrity

Description

• Clarify business requests for assistance and document business requirements taking a broad perspective to identify solutions.
• Carries out data mining using state-of-the-art methods.
• Enhance data collection procedures to include information that is relevant for building user solutions by processing, cleansing, and verifying the integrity of data used for analysis.
• Collaborates and builds productive relationships with various internal and externa departments to understand departmental issues and provides solutions to moderately complex problems.
• Effectively communicates and collaborates across groups to provide insights to the organization.
• Implement new statistical or other mathematical methodologies as needed for specific models or analysis.
• Devise possible solutions and plan solution development.
• Optimize joint development efforts through appropriate database use and project design.
• Provides leadership for cross-functional projects and enterprise data and analytics solutions.
• Performs ad-hoc analysis and presenting results in a clear manner.
• Develop production quality complex analytics and machine learning models where analysis of data requires the evaluation of a multitude of factors.
• Collaborates and contributes to data science standards and methodologies.
• Participate in data science mentoring efforts.
• Manages multiple large scale, end-to-end data science projects simultaneously.

Requirements

• Experience with Machine Learning, Data Science algorithm visualization.
• Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
• Functional knowledge of cloud platforms such as AWS.
• At least three years of experience leading Data Science projects.
• Experience with creating project overviews and effort estimates.
• Experience building, tuning, and managing the creation of machine learning models for business applications including data cleansing, ordering and tagging (data wrangling).
• Strong communication skills and the ability to naturally explain difficult technical topics to everyone from data scientists to engineers to business partners.
• Solid experience with data scripting languages such as Python, and R. Experience in SQL and data manipulation techniques.
• Ability to present findings in the data in a clear and concise manner, using visualization (e.g. creating dashboards) and narrative formats.
• SQL and NOSQL experience.
• Experience with working with AWS, Azure or other cloud-based platforms.
• Experience with mentoring data scientists and business users.
• Experience with prioritizing multiple small Data Science initiatives.
• Natural curiosity and desire to learn, a passion for solving real world problems.
• Graduate degree in quantitative field
• Experience working with SAP HANA database and using HANA studio.
• Solid understanding of Machine Learning techniques such as Regression, clustering, decision trees, random forests, NLP, etc.
• Strong organizational and multitasking skills with ability to balance competing priorities.
• Bachelor’s degree in Computer Science, mathematics, statistics, economics, finance, Data Science or other relevant quantitative field; or equivalent experience
• Experience working with SAP data.

Benefits

Training + Development

Interview process

Visa Sponsorship

Security clearance