Sr. Data Scientist - Analytics (Hybrid)
Our client, a leading Pacific Northwest utility provider committed to public service and environmental preservation, is looking for a Sr. Data Scientist - Analytics for their Vancouver, WA location. This
position will work within the Transmission Infrastructure Asset Management organization on the Strategy and Planning team. Support projects under the program by providing analytical expertise for planning, development, integration, and implementation of asset management technologies, methods, and standards for interim and long-term solutions to manage risk and spend efficiency on the transmission system. Will analyze, process and model data and interpret the results to develop data-driven solutions.

This hybrid position is a one-year renewable contract that includes employee benefits! If you feel this position aligns with your professional experience, we want to hear from you!

Key Responsibilities for Sr. Data Scientist - Analytics:

Works closely with asset management teams to identify and answer crucial strategic asset management questions, leading efforts to provide data-driven insights that support and inform broad strategic initiatives.
Drives the development of innovative data solutions to extract, analyze and model data to solve or answer previously unanswered problems of a complex and nuanced nature.
Introduce new analytical and predictive models and methodologies that serve to establish new best practices in day-to-day operations.
Employs mastery of a broad range of advanced methods in mathematics, statistics, computer science, and machine learning to develop best-in-class analytical techniques for modeling complex patterns in a variety of data types.
Explains and shares model output to impacted and interested operational and executive parties and stakeholders.
Develops and applies innovative statistical and mathematical principles and concepts along with appropriate testing and prototyping programs.
Reviews analytics created by others, provide advice and consultation, and lead independent verification of results, when needed.

Requirements/Qualification for Sr. Data Scientist - Analytics:

A Bachelor’s or Master’s degree in advanced mathematics, computer science, machine learning, or statistical methods is required.
- With a Master’s degree, 7 years of hands-on experience performing the following is required.
- With a Bachelor’s degree, 9 years of experience is required.
7+ years of hands-on experience in the following skills:
- Manipulating data sets, querying databases, and building statistical models
- Statistical or data mining techniques
- Using Web Services
- Analyzing data from 3rd party users
- Developing data models and algorithms
- Creating and using advanced machine learning algorithms and statistics
- Knowledge and understanding of financial analysis/budgeting, risk analysis, probability and statistics, and electric utility operations
With a Bachelor’s degree, at least 10 graduate credits in computer science algorithms, statistics, software design, or data management OR one of the following Data Science Certifications or similar are required:
- Certified Analytics Professional (CAP)
- Data Science Council of America (DASCA) Senior Data Scientist (SDS)
- Data Science Council of America (DASCA) Principle Data Scientist (PDS)
- Dell EMC Data Science Track
- Google Certified Professional Data Engineer
- Google Advanced Data Analytics Certificate for Machine Learning
- IBM Data Science Professional Certificate

Mathematics experience including multivariate calculus, linear algebra, differential equations, and real analysis:
- Probability and Statistics: including stochastic processes, classical inference techniques, maximum likelihood estimation, Bayesian methods, Monte Carlo, and bootstrapping.
- Computer Science: design and analysis of algorithms and data structures, computational complexity, search methods.
- Supervised Learning (e.g., regression techniques, regularization techniques, ridge regression, ensemble methods, optimization through linear programming and convex optimization, nonlinear programming).
- Unsupervised Learning (e.g., clustering techniques, hierarchical clustering, dimensionality reduction, principal component analysis).
- Time Series Analysis.
Demonstrated knowledge of computer languages including, but not limited to Python, Java, SQL, and R. Demonstrated knowledge of distributed or parallel processing techniques used in the analysis and processing of large data sets.
Skill in discerning the strengths and weaknesses of various best-practice quantitative solutions for a given real-world problem and skill in developing new quantitative approaches to cater to particular features as needed.
Using considerable judgment, proven ability to take vague or broadly defined goals or business objectives and translate them to questions that can be answered or problems that can be addressed via data driven analysis.
Demonstrated ability to communicate and present proposals, findings, and recommendations, both written and orally, to senior staff, management and executives and to external parties.

**We are unable to accommodate corp. to corp. candidates**

About Motus Recruiting and Staffing, Inc:
Founded in 2006, Motus is an award-winning recruiting and staffing firm in the Pacific Northwest, specializing in professional services and technology solutions. We are a group of people who not only recognize the importance of representation, but actively fight for diversity, equity, and inclusion in the recruitment process. Our goal is to educate organizations on the importance of DEI when hiring, promoting, and supporting diverse employees. We are calling organizations to demonstrate their commitment to DEI by being intentional about who they hire.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, citizenship, disability or protected veteran status.

ED/BH 14096

Job ID: 14096

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Sr. Data Scientist - Analytics (Hybrid)