Principal Data Scientist-Foundry Exp. (W2 Contract)

Principal Data Scientist 12 months+ contract Oakland, CA-Hybrid (one day per week onsite) • • • • Local Candidates Only • • • • Equipment: Client' laptop will be provided upon start (or within a few days). If delayed, personal device may be used via Citrix/VD I Top Skill • s:Pyspark Proficien • cyUser Interface Development Proficien • cyStrong Cross-Functional Collaboration Skil lsQualificatio nsMinimu • m:Master’s Degree in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent fiel • d.Experience in Data Science, 8 years or 2 years experience, if possess Doctoral Degree or higher in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent fiel d.Desire • d:Doctorate Degree in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent fiel • d.Expertise in experimental design and causal inference method • s.Expertise in statistical methods for time series analysis, statistical modeling, and probabilistic risk assessmen • t.Relevant industry experience (electric or gas utility, data science consulting, etc • .)Familiarity with the use of supervised, unsupervised, deep learning & physics-based methods for modeling electrical infrastructure failure mode • s.Competency with data science standards and processes (model evaluation, optimization, feature engineering, etc) along with best practices to implement th • emKnowledge of industry trends and current issues in job-related area of responsibility as demonstrated through peer reviewed journal publications, conference presentations, open source contributions or similar activiti • esCompetency with Agile product development best practice • s.Proficiency with Python or Pyspark, code reviews, and code development best practice • s.Proficiency in explaining in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipeline • s.Mastery in clearly communicating complex technical details and insights to colleagues and stakeholde • rsAbility to develop, coach, teach and/or mentor others to meet both their career goals and the organization goa lsPosition Summar y:Leads the design, development, and execution of scripts, programs, models, user interfaces, algorithms, and processes, using structured and unstructured data from disparate sources and sizes, generating for defensible, valid, scalable, reproducible and documented machine learning and artificial intelligence models (predictive or optimization) for problem solving and strategy development. Educates the non-technical community on advantages, risks, and maturity levels of data science solution s. Job Responsibiliti • es:Researches and applies advanced knowledge of existing and emerging data science principles, theories, and techniques to inform business decisio • ns.Creates advanced data mining architectures / models / protocols, statistical reporting, and data analysis methodologies to identify trends in structured and unstructured data s • etsExtracts, transforms, and loads data from dissimilar sources from across client for their machine learning feature engineer • ingApplies data science/ machine learning /artificial intelligence methods to develop defensible and reproducible predictive or optimization models that involve multiple facets and iterations in algorithm developme • nt.Wrangles and prepares data as input of machine learning model development and feature engineer • ingArchitects, develops, and documents reusable functions and modular code for data scien • ce.Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analys • is.Works with stakeholder departments and company subject matter experts to understand application and potential of data science solutions that create val • ue.Presents findings and makes recommendations to senior manageme • nt.Act as peer reviewer of complex mod els