Data Scientist

NOV • Houston, TX

7d

About The Position

The Data and Analytics team works with people across the organization to identify, assess, and solve real business problems by analyzing all available data, including enterprise, connected product, and publicly available datasets, to create and discover meaningful insights. The Data Scientist will be responsible for guiding successful delivery of Data Science and Analytic solutions to internal customers. As a Data Scientist , you will: Collaborate with business stakeholders to understand business problems, formulate requirements and rationalize analytical approaches to solve them Develop a firm understanding of specific business processes and real-world workflows, which may include manufacturing, supply chain, accounting and other related functions Clean, process and wrangle raw data into usable formats for analysis and modeling Conduct exploratory data analysis to identify trends, patterns, and insights from complex datasets Perform statistical analysis and hypothesis testing to validate data-driven hypotheses Assist in the development and implementation of machine learning models for predictive and prescriptive analytics Collaborate with Senior Data Scientists to refine and optimize existing models Contribute to feature engineering efforts to enhance the predictive power of machine learning models Explore and experiment with different feature selection techniques Work closely with cross-functional teams including domain experts, business analysts, data engineers and software engineers Communicate findings and insights to non-technical stakeholders in a clear and understandable manner Utilize programming languages such as SQL, Python for data manipulation, analysis and model development

Requirements

• Bachelor's degree in a quantitative discipline (e.g., Business Analytics, Computer Science, Data Science, Economics, Industrial Engineering, Math, Statistics or related field)
• Two or more years of relevant work experience, mining data as a data analyst or scientist or in a business role with a heavy focus on analytics or statistics
• Strong analytical, quantitative, and problem-solving skills
• Proven ability to communicate complex or technical concepts clearly to both technical and non-technical audiences
• Programming experience with SQL and Python is a must
• Modeling experience with core data science packages (Pandas, Scikit-learn, Keras, TensorFlow, etc)
• Experience with core visualization packages (Matplotlib, Seaborn, Plotly, etc)
• Ability to work independently, exercise initiative, and follow through to accomplish tasks
• Ability to manage adjusting priorities and work on multiple projects simultaneously while addressing ad hoc data requests

Nice To Haves

• Familiarity with manufacturing daily operations and related data sources, including ERP systems and related table structures
• Modeling experience with traditional machine learning and deep learning techniques
• Experience with productizing machine learning models within a cloud service (e.g. AWS, Azure) and data science environments (e.g. Databricks) is a plus
• Programming experience with PySpark is a plus

Responsibilities

• Collaborate with business stakeholders to understand business problems, formulate requirements and rationalize analytical approaches to solve them
• Develop a firm understanding of specific business processes and real-world workflows, which may include manufacturing, supply chain, accounting and other related functions
• Clean, process and wrangle raw data into usable formats for analysis and modeling
• Conduct exploratory data analysis to identify trends, patterns, and insights from complex datasets
• Perform statistical analysis and hypothesis testing to validate data-driven hypotheses
• Assist in the development and implementation of machine learning models for predictive and prescriptive analytics
• Collaborate with Senior Data Scientists to refine and optimize existing models
• Contribute to feature engineering efforts to enhance the predictive power of machine learning models
• Explore and experiment with different feature selection techniques
• Work closely with cross-functional teams including domain experts, business analysts, data engineers and software engineers
• Communicate findings and insights to non-technical stakeholders in a clear and understandable manner
• Utilize programming languages such as SQL, Python for data manipulation, analysis and model development

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees