Company: BP
Skills: IT - Analysis & Management
Education: Masters Degree
Employment Type: Full Time Salaried Employee
Location: Houston, Texas, United States

In order to apply for this position, applicants MUST meet the following criteria. If your resume does not match these criteria, you will not be able to apply for this position.

Enhance our ability to find performance insights through the use of advanced data science metholodogies, tools, and approaches to leverage artificial intelligence technologies and techniques.
  • The Data Scientist (Engineer) supports the data and analytics value chain and GOO dashboards, providing real-time access to performance data to support the organizations ability to find insights from our data.
  • Support the Analytics Community of Practice
  • Sustain and improves GOO Intelligence
  • Works collaboratively across the Performance sub-function so that the analytical tools delivered meet the needs of the Analyst.
  • Data Scientists (Engineers) Creates machine learning models that deliver value to all areas of Operation via modern statistical techniques, including: Regression, Support Vector Machines, Regularization, Boosting, Random Forests and other Ensemble Methods, leveraging high-level languages, such as R, Python, Perl, Ruby and Scala
  • Deploy models via APIs into applications or workflows
  • Deliver functional proof-of-concepts for GOO
  • Discover hidden insights/embedded patterns to enable business stakeholders to make more informed decisions
  • Collaborate with data architects and developers to define architectures and select technologies
  • Data Scientists (Engineers) contribute to the overall prescriptive strategy and goal development for Machine Learning/ AI automation
Education Required:
  • Higher education degree (Masters, or PhD) in Business, MIS, Mathematics, or Engineering preferred
Experience and Job Requirements:
  • A deep knowledge of performance management and reporting systems, machine learning, AI, etc.
  • A strong working knowledge of various systems and processes utilised within our industry
  • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
  • Experience building and optimizing 'big data' data pipelines, architectures and data sets.
  • Strong analytic skills related to working with structured and unstructured datasets.
  • Build processes supporting data transformation, data structures, metadata, dependency and workload management.
  • A successful history of manipulating, processing and extracting value from large datasets.
  • Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores.
  • Experience using the following software/tools:
    • Big data tools: Hadoop, Spark, Kafka, etc.
    • Relational SQL and NoSQL databases, including Postgres and Cassandra.
    • Hands on experience in Azure and AWS cloud services: Databricks, EC2, EMR, RDS, Redshift, ADS.
    • Data pipeline and workflow management tools: Airflow, Logic Apps, Data Factory, etc.
    • Extensive experience in Scripting languages and general-purpose languages: Python, R, JavaScript, Scala, C++, C#, etc.
    • O365 data tools: PowerApps, Flow, SharePoint Online, etc.
    • Experience with data visualization tools for the design and development of dashboards, reports, and front-end visualizations: Power BI, Spotfire, etc.