About
Gather and analyze large sets of structured and unstructured data. A data scientist's role combines computer science, statistics, and mathematics. They analyze, process, and model data then interpret the results to develop data-driven solutions and create actionable plans for companies and organizations. Work includes the collection, cleaning and formatting of data to meet the company's purpose. Duties vary according to the industry and may include experimental frameworks for product development and machine learning with the aim to lay a strong data foundation for robust analytics to be performed. Position Responsibilities
Analyze competitive market strategies through analysis of related product, market or share trends. Synthesize current business intelligence or trend data to support recommendations for action. Communicate with customers, competitors, suppliers, professional organizations or others to stay abreast of industry or business trends. Manage timely flow of business intelligence information to users. Collect business intelligence data from available industry reports, public information, field reports, or purchased sources. Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies. Identify and analyze industry or geographic trends with business strategy implications. Analyze technology trends to identify markets for future product development or to improve sales of existing products. Generate standard or custom reports, summarizing business, financial or economic data for review by executives, managers, clients and other stakeholders. Identify or monitor current and potential customers, using business intelligence tools. Maintain or update business intelligence tools, databases, dashboards, systems or methods. Solve business related problems/challenges while using data-driven techniques and tools. Communicate findings and provide recommendations using data visualizations and comprehensive reports. Create data visualizations, dashboards, and other data presentations relative to a variety of audiences, from high-level, strategic results, with an ability for a deep dive into data details. Identify patterns and trends in data; providing a plan to implement solutions. Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes. Contribute to data mining architectures, modeling standards, reporting and data analysis methodologies. Develop custom data models and algorithms to apply to data sets, solve problems and build analytical tools. Develop company A/B testing framework and test model quality. Coordinate with different functional teams to implement models and monitor outcomes. Develop processes and tools to monitor and analyze model performance and data accuracy. Recommend cost-effective changes to existing procedures and strategies. Position Requirements
Education & Corresponding 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
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, 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
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 regionally such as to key stakeholders, customers, industry organizations, or regulators). Preferred Technical 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). Everest Consultants offers the following benefits for this position: medical, dental, & vision insurance, short-term disability, life and AD&D insurance, a 401(k) retirement plan, and a referral bonus program, paid sick/vacation/holidays, and a health and welfare fringe benefit. Everest Consultants is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, disability, or any other characteristic protected by applicable local, state, or federal civil rights laws.
Languages
- English
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