Manufacturing Data Scientist

Must live in the Portland Metro region

Role Responsibilities:

• Proposes solutions and strategies to business challenges; Independently works on a wide range of complex problems that require new approaches through adaptation and modification of standard data, analytics, and data science principles, theories, techniques, and procedures, providing solutions that are imaginative, thorough, and practical.
• Design, implement, test, deploy, and maintain stable, secure, and scalable data engineering solutions and pipelines in support of data and analytics projects, including integrating new sources of data into our central data warehouse and moving data out to applications.
• Undertakes preprocessing of structured, semi-structured, and unstructured data
• Analyzes large amounts of information to discover trends and patterns
• Builds predictive models and machine-learning algorithms
• Selects features, builds, and optimizes classifiers using machine learning techniques
• Combines models through ensemble modeling
• Works with engineering and product development teams to deliver insights through predictive analytics
• Performs data mining using state-of-the-art methods
• Analyzes data, analytics, and BI problems to determine suitable solutions. Establishes and coordinates design reviews with peers and project leads. Responsible for organizing data and preparing documentation for assigned projects.
• Responsible for thoroughly testing data, analytics, and machine learning solutions
• Most work is examined at a higher level. Actual supervision received may be minimal or moderate, depending upon project complexity. Closer supervision is given on new aspects of assignments.

Qualifications:

• At least ten years of experience in the field of data science
• Proven track record of applying data science techniques to solve complex problems.
• Five years of experience coding in Python including comprehensive knowledge of Pythian libraries, applications and use cases for data prep and analysis (e.g. Pandas, NumPy )
• Thorough knowledge of statistical methods and their applications
• In-depth knowledge and expertise in machine learning algorithms and frameworks (e.g. TensorFlow, PyTorch, Scikit-learn)
• Experience leading projects and mentoring junior data scientists or analysts.
• Strong command of relational databases, SQL and ETL best practices
• In-depth understanding of data lakes, data pipelines, and data science applications
• Comprehensive knowledge of working with structured, semi-structured and unstructured data to develop and deploy predictive models and machine learning solutions
• Ability to interpret moderately complex data, analytics, and data science requirements and apply data, analytics, and machine learning methodologies.
• Proficient in general data manipulation tasks, including reading, processing, and cleaning data; transforming and recoding variables; merging multiple datasets; and reformatting data between wide and long formats
• Demonstrated ability to learn new techniques and troubleshoot code wit

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.