Position Title: Data Scientist II
Position Description: Protingent Staffing has an exciting direct hire opportunity with our client in Bend, Oregon.
Lead discovery processes of high complexity with stakeholders to define the business problem, understand IT and business constraints and opportunities and understand the qualitative nature of data required to deliver results.
Transform the business problem into an analytical problem and identify a wide breadth of data science approaches for achieving the desired business insights and criteria for selecting among approaches.
Build data pipelines from sources including internal data (i.e., point-of-sale, ERP and financial systems, websites, etc.) and external data (i.e., weather stations, geo-location systems and social media sites).
Apply data cleansing techniques such as deduplication, hashing, scaling and normalization, dimensionality reduction, fuzzy matching, imputation and cross-validation.
Design experiments to gain insight and test hypotheses using quantitative methods.
Apply various Machine Learning (ML) and advanced analytics techniques to perform classification or prediction tasks.
Present insights and rationale of recommendations in easy to understand terms; guide business stakeholders to validate insights and recommendations; maintain an ability and willingness to present analysis results that are data driven and may contradict common belief.
Collaborate with data engineers and IT to evaluate and implement deployment options for developed models.
Identify the lifecycle of any developed models and insights and develop maintenance plans for ongoing operational use of insights and recommendations.
Assist the Data Science and BI team lead in creating high quality summaries of Data Science projects and results for presentation to steering committees and executive groups
Assist the Data Science and BI team lead in scoping and prioritizing data science projects
Create reusable artifacts and contribute to data and insight catalogues and documentation
Be a lead participant in peer reviews and presentation of specialist data science topics to advance collective team understanding of relevant technologies and techniques to accomplish data science outcomes
Network within IDS and business partner departments to gain business understanding
Proactively engage in continuous professional improvement in both technical and soft skills
Partner with data stewards and data platform developers in continuous improvement processes to help improve data quality
Recommend ongoing improvements to data capture methods, analysis methods, mathematical algorithms, etc. that lead to better outcomes and quality.
Contribute to group retrospectives and improvement of processes for collective work management
Help improve enterprise stakeholder understanding of related technologies and processes to accomplish data science outcomes
Guide and inspire others about the potential applications of data science
Bachelor’ s degree in applied mathematics, statistics, computer science, operations research, or a related quantitative field. Alternate experience and education in equivalent areas such as economics, engineering or physics is acceptable.
Master’ s degree preferred
Certified Analytics Professional credential (available through INFORMS.ORG) required
AND minimum of 3-6 years of full-time or equivalent relevant experience executing data science projects, preferably in the domains of customer behavior prediction and operations management.
Advanced coding knowledge and experience in at least two programming languages: for example, R, Python/Jupyter, C/C++, Java or Scala.
Advanced knowledge of database programming languages including SQL, PL/SQL, or others for relational databases, graph databases or NOSQL/Hadoop-oriented databases.
Broad Knowledge and experience in statistical and data mining techniques that include generalized linear model (GLM) / regression, random forest, boosting, trees, text mining, hierarchical clustering, neural networks, graph analysis, data sampling, design of experiments, etc. Familiarity with typical algorithms used by retail businesses (i.e., Churn, Segmentation) required.
Technical skills for working across multiple deployment environments including cloud, on-premises and hybrid and skills for acquiring new datasets, parsing datasets, organizing datasets, representing data visually and automating data-driven models.
Advanced knowledge of statistical tools and advanced analytics platforms such as: Minitab, SAS, Knime, Dataiku, Anaconda, Google Collaboratory
About Protingent: Protingent is a niche provider of top Engineering and IT talent to Software, Electronics, Medical Device, Telecom, and Aerospace companies nationwide. Protingent exists to make a positive impact and contribution to the lives of others as well as our community by providing relevant, rewarding, and exciting work opportunities for our candidates.View More
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