Data Scientist - Analytics

APR Staffing

Vancouver, WA

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JOB DETAILS

SKILLS

Algorithms, Analysis Skills, Asset Management, Background Investigation, Bayesian Networks, Best Practices, Budgeting, Business Intelligence, Calculus, Communication Skills, Computer Science, Data Analysis, Data Management, Data Mining, Data Modeling, Data Processing, Data Science, Data Sets, Data Structures, Dell Computers, Differential Equations, Documentation Models, Driver's License, Electrical Utility, Energy & Utilities, Expense Management, Financial Analysis, Geographic Information Systems (GIS), IBM Product Family, Java, Linear Algebra, Machine Learning, Mathematics, Microsoft Product Family, Monte Carlo Method, Parallel Computing, People Management, Power BI, Predictive Modeling, Presentation/Verbal Skills, Principal Component Analysis (PCA) , Procedure Development, Process Analysis, Process Modeling, Prototyping Programming Languages, Python Programming/Scripting Language, R Programming Language, Ridge Regression, Risk Analysis, Risk Management, SQL (Structured Query Language), Software Design, Statistical Algorithms, Statistical Modeling, Statistics, Statistics Software, Strategic Planning, Technical Recruiting, Technical Writing, Time Series Analysis, Trend Analysis, United States Citizen, Web Services, Willing to Travel

LOCATION

Vancouver, WA

POSTED

1 day ago

Job Title: Data Scientist - Analytics
Job Number: 11957
Location: Vancouver, WA
Hybrid: onsite - 3 days per Week, 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%
Travel: Up to 15% to local meetings/trainings
Length: 5 years

MUST be US Citizen to be eligible to apply for Federal Background Check

Requires Real ID and or Valid Passport to interview

SUMMARY

The full-time contract Data Scientist assignment will work within the corporate Transmission Infrastructure Asset Management organization on the Strategy and Planning team. This assignment will provide support for projects under the division's 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 corporate transmission system. This assignment will analyze, process and model data and interpret the results to develop data-driven solutions

POSITION RESPONSIBILITIES

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 corporate 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 & Experience:

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 Skills & Experience

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 the client regionally such as to key stakeholders, customers, industry organizations, or regulators).

Preferred Skills & Experience

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:

Valid U.S. Driver’s License is required

Pre-Employment Requirement
All employment offers are contingent upon successful completion of our pre-employment screening that may include drug testing, background/criminal check, and if applicable, must meet eligibility requirements for access to classified information.

APR Staffing is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

About APR Staffing
APR Staffing was born from the merger of two well-respected technical staffing firms in Portland. ieSolutions and Data Resource Group. Both companies have recently been award winners for the Portland Business Journal's Fastest-Growing Private Companies. The two firms, now as APR Staffing, make for one of the fastest-growing and most-respected professional and technical staffing companies in Oregon and Southwest Washington.

Collaborating with our customers, we augment their workforce with technical and administrative professionals. We provide only high-caliber, professional-grade resources throughout the Pacific Northwest.

About the Company

APR Staffing

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