United States onlyThe Data Scientist will provide meaningful insight on how to improve our
current business operations.
Principle Accountabilities/Responsibilities
- Work closely with domain experts and SME’s to understand the business problem or opportunity and assess the potential of machine learning to enable accelerated performance improvements
- Design, build, tune, and deploy divisional AI/ML tools that meet the agreed upon functional and non-functional requirements within the framework established by the Enterprise IT and IS departments.
- Perform large scale experimentation to identify hidden relationships between different data sets and engineer new features
- Communicate model performance & results & tradeoffs to stake holders
- Determine requirements that will be used to train and evolve deep learning models and algorithms
- Visualize information and develop engaging dashboards on the results of data analysis.
- Build reports and advanced dashboards to tell stories with the data.
- Lead, develop and deliver divisional strategies to demonstrate the: what, why and how of delivering AI/ML business outcomes
- Build and deploy divisional AI strategy and roadmaps that enable long-term success for the organization that aligned with the Enterprise AI strategy.
- Proactively mine data to identify trends and patterns and generate insights for business units and management.
- Mentor other stakeholders to grow in their expertise, particularly in AI / ML, and taking an active leadership role in divisional executive forums
- Work collaboratively with the business to maximize the probability of success of AI projects and initiatives.
- Identify technical areas for improvement and present detailed business cases for improvements or new areas of opportunities.
Qualifications/Education/Experience Requirements
- PhD or master’s degree in Statistics, Mathematics, Computer Science or other relevant discipline.
- 5+ years of experience using large scale data to solve problems and answer questions.
- Prior experience in the Manufacturing Industry.
Skills/Competencies Requirements
- Experience in building and deploying predictive models and scalable data pipelines
- Demonstrable experience with common data science toolkits, such as Python, PySpark, R, Weka, NumPy, Pandas, scikit-learn, SpaCy/Gensim/NLTK etc.
- Knowledge of data warehousing concepts like ETL, dimensional modeling, and sematic/reporting layer design.
- Knowledge of emerging technologies such as columnar and NoSQL databases, predictive analytics, and unstructured data.
- Fluency in data science, analytics tools, and a selection of machine learning methods – Clustering, Regression, Decision Trees, Time Series Analysis, Natural Language Processing.
- Strong problem solving and decision-making skills
- Ability to explain deep technical information to non-technical parties
- Demonstrated growth mindset, enthusiastic about learning new technologies quickly and applying the gained knowledge to address business problems.
- Strong understanding of data governance/management concepts and practices.
- Strong background in systems development, including an understanding of project management methodologies and the development lifecycle.
- Proven history managing stakeholder relationships.
- Business case development.
First Quality is committed to protecting information under the care of First Quality Enterprises commensurate with leading industry standards and applicable regulations. As such, First Quality provides at least annual training regarding data privacy and security to employees who, as a result of their role specifications, may come in to contact with sensitive data.
First Quality is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, sexual orientation, gender identification, or protected Veteran status.
