*** | SUPPLEMENTAL LABOR MANAGEMENT OFFICE
ADDITIONAL PROCUREMENT INFORMATION (API)
Title & Level
Data Scientist
Work Group Location
Vancouver, WA
Specialty
Analytics
Offsite Work Eligibility*
Routine Telework Eligible
Organization
TIS
Number of Days Onsite
~3 days per Week
Hours
Full-Time, up to 40 hours
Additional Information
Position approved for Telework on Mondays and Fridays. In the office attendance required Tuesday, Wednesday and Thursday each week. Mondays and Fridays may potentially require some onsite days based on training / project / workload needs or as requested.
Overtime
15% anticipated
On-Call
No
Travel
Up to 15% to local meetings/trainings
FN Status
NOT open to Foreign Nationals
* Current telework, remote work and onsite support is based on BPA's business needs and is subject to change or termination at any time.
OVERVIEW
Assignment
The full-time contract Data Scientist assignment will work within ***'s (BPA's) Transmission Infrastructure Asset Management (TI) organization on the Strategy and Planning (TIS) team. This assignment will provide support for projects under the TI 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 BPA's transmission system. This assignment will analyze, process and model data and interpret the results to develop data-driven solutions.
Organization
The TIS organization provides strategic asset management direction through risk-informed based investment asset plans, 10-year transmission infrastructure strategies, asset risk evaluation and application, and infrastructure resiliency planning. Candidates should be self-starters, motivated to work independently in a collaborative manner with their own team members and internal stakeholders. The ideal candidate should enjoy working under pressure and timelines, while maintaining accuracy and excellent records management. This position is very busy, resides in a fast-paced environment, and manages multiple projects/tasks with the ability to adapt to change.
ASSIGNMENT RESPONSIBILITIES
Note: All official drafts, documents and recommendations, as listed below, must be reviewed, finalized and approved / accepted by appropriate BPA manager or other federal personnel with the authority to do so.
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.
Develops and recommends innovative approaches and new solutions for data access, maximization and utilization and identifies emergent trends and opportunities for future development.
Performs research to design and implement efficient algorithms for extracting information from large quantities of raw data across numerous disparate and potentially conflicting data sources.
Performs independent studies and assessments to evaluate the effectiveness and efficiency of new computational and storage technologies in comparison to current systems capabilities.
Provides useful visuals and executive summaries as a technical advisor to senior management and other stakeholders.
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.
Provides technical expertise on analytics that address BPA and industry specific questions.
Create procedural and technical documentation of models before handing over routine model running to reporting personnel.
Reviews analytics created by others, provide advice and consultation, and lead independent verification of results, when needed.
Facilitates coordination of assumptions, data and selection of methodologies.
REQUIREMENTS
Education & Corresponding Experience (required on matrix)
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:
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 also 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
Required Technical Skills & Experience (required on matrix)
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 when standard assumptions are inappropriate.
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 (e.g., representing BPA regionally such as to key stakeholders, customers, industry organizations, or regulators).
Preferred Skills & Experience (optional on matrix)
Knowledge of GIS and Asset Management Systems.
Experience with R software product(s).
Energy/utility industry experience.
Experience with Power BI (Microsoft Business Intelligence).
Additional Requirements (not required on matrix)
Valid U.S. Driver's License is required.
Appendices
The following appendices apply to this assignment and may be downloaded from the Fieldglass Reference Library:
Offsite Work
Training Expectations (Worker is expected to keep current on the latest technologies and skills required for the assignment.)
Training Type
Details
Provided by
Asset Suite
BPA
Cascade
BPA
Power BI
BPA
Attendance at all conferences, workshops, training, etc. must be pre-approved by SLMO. Requests will be reviewed on a case-by-case basis. Approval is subject to the most current guidance provided to SLMO by BPA or DOE and is subject to change at any time. SLMO reserves the right to negotiate attendance on billable/non-billable hours and reimbursement of travel costs with the supplier. Reimbursable travel costs must adhere to the Federal Travel Regulations and be submitted via an expense sheet in Fieldglass.