Data Scientist
- 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
- 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; additional programming experience with PySpark is a plus
- Modeling experience with core data science packages (Pandas, Scikit-learn, Keras, TensorFlow, etc)
- Experience with core visualization packages (Matplotlib, Seaborn, Plotly, etc)
- Strongly preferred: 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
- 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
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