Expert Data Scientist - Center of Excellence in Data Science Artificial Intelligence
Expert Data Scientist - Center of Excellence in Data Science Artificial Intelligence
Posted on :
14-01-2025
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Monthly Salary
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Salary Not Disclosed
Vacancy
1 Vacancy
Posted on :
14-01-2025
Job Description
Overview:
TekWissen is a global workforce management provider headquartered in Ann Arbor Michigan that offers strategic talent solutions to our clients worldwide. This Client is a holding company that primarily operates through Gas and Electric Company subsidiary. The subsidiary provides natural gas and electric service to residential and business clients. It also offers building and construction programs energy efficiency financing electric vehicle charge networks wireless solutions battery storage systems etc. This Client is an AA/EEO employer that actively pursues and hires a diverse workforce.
Job Title: Expert Data Scientist Center of Excellence in Data Science & Artificial Intelligence
Location: Oakland CA 94612
Duration: Full Time
Job Type: Full Time
Work Type: Hybrid
Job Description:
- This team works on a wide variety of difficult problems offering great variety in the work and constant opportunity to explore and learn. Current and past engagements include:
- Creating wildfire risk models that are used by regulators and the utility to prioritize asset management
- Developing computer vision models that improve accelerate and automate asset inspections processes
- Predicting electric distribution equipment failure before it occurs allowing for proactive maintenance
- Forming the analytical framework behind clients Transmission Public Safety Power Shutoff
- Optimizing nonwires alternative resource portfolios like the Oakland Clean Energy Initiative including location and resource adequacy considerations
- Analyzing customer demographic program participation and SmartMeter interval data to build program targeted propensity models e.g. for customer owned distributed energy resource technologies
- Identifying and investigating anomalous customer natural gas usage in order to resolve dangerous customer side leaks
Position Summary:
- We are seeking two (2) experienced data scientist to join client as expert members of companys Center of Excellence in Data Science & AI.
- Each technical leadership role has an unparalleled opportunity to influence the success of data science and related AI technical fields (ML and GenAI) across a large diverse company with an essential societal mission.
- Each role is perfectly suited for a candidate with deep experience leading technical portfolios focusing on AI/ML/GenAI modeling work and who would now like to make a contribution to the data science community by supporting teams across the company rather than delivering solutions directly.
- A desire and aptitude for consulting mentoring advising educating influencing and relationship building is strongly needed.
- This technical leader will be an individual contributor who possesses a drive to keep their skills sharp through continuous education and research as they assist with a wide variety of advance data science and analytics projects across the company.
- Study and continuous assessment of emerging technologies will facilitate thought leadership and influence technical roadmaps.
- Strictly data scienceAI/ML/GenAI algorithmrelated software engineering skills are desired with experience developing productionready code and managing data science products through the delivery cycle.
- Emphasis will be placed on a knowledge of and experience with algorithms theory measurement and evaluation coding tooling data systems and support environments specific to data science and AI.
- Successful candidates may come from diverse backgrounds including data science ML engineering software engineering physical sciences and others (education requirements listed below).
- This role will also make contributions to the development and implementation of standards processes governance frameworks guidelines and operational product excellence (i.e. AI/ML/GenAI product lifecycle evaluation along with scalability validity and other performance measures).
- Finally another critical component of this profile is AI/ML/GenAI model evaluation and performance assessment when vendors or thirdparty developers formulate proposals or develop solutions for internal Functional teams.
Job Responsibilities
- As part of the centralized Hub team support data science AI/ML/GenAI and advanced analytics Spokes across the company by spearheading the implementation of best practices in the development of AI/ML/GenAI and other advanced data science and analytics models in aspects such as code engineering and best practices in coding statistical and probabilistic problem modeling product scalability AI/ML/GenAI model evaluation and the like.
- Support the design implementation and continuous improvement of governance tools (policies standards and processes) for the effective and safe development of AI/ML/GenAI and data science models as a product. Continuously educate Spokes on governance requirements. Monitor compliance and escalate as needed.
- Development of governance documents (policy standards and processes) for emerging and disruptive technologies such as Generative AI Foundational Models automation and hyperautomation technologies etc. Keeping abreast of existing AI and other emerging technology regulations at the state and national level to pivot internal compliance.
- Develop and maintain an emerging technologies evaluation toolkit to assess technology maturity level and its readiness for value realization of business goals. Current focus of said toolkit revolves around Generative AI and automated decision making by AI algorithms monitoring elements such as model hallucinations and misinformation training biases etc.
- In crosscollaboration with the Enterprise Strategy and Architecture team Functional Areas and other players in product acquisition support vendor and thirdparty proof of concept proposal and product assessment from a technical perspective mainly (but not exclusively) on AI/ML/GenAI model design and approach performance measure metrics technical maturity etc.
- Support the Peoples Organization (HRBP & Compensation) in the analysis of data science competencies continuously monitoring the evolution of the industry and advising on skill fitness to current data science work planned enterprisewide.
- Continuous dissemination and active participation in the internal and external data science community of practice leading the development of knowledge that advances the field. Leading emerging communities of practice (such as the Generative AI CoP) to disseminate knowledge and generate networks internally and externally.
- Advise and consult delivery teams in the optimal implementation of advanced technologies as proof of concept balancing risk and innovation to accomplish business goals.
- Support the identification and implementation of process improvement at the department (EDS&AI) level. Support the adoption of Lean methodologies across EDS&AI.
- Support building data science capability by advising Hub teams as well as Spokes across the enterprise with the end goal to contribute to improved decisionmaking in all functional areas.
- Present findings and make recommendations to officers and crossfunctional management.
- Educate the internal community (including Executives) on emerging trends. Continuously monitor new technologies and assess their impact and potential disruption to business programs.
- Effectively communicate a compelling vision of data science and AI/ML/GenAI technologies that add value to the company.
- Build and maintain strong relationships with business units and external agencies.
Additional General Job Responsibilities
- Researches and applies advanced knowledge of existing and emerging data science principles theories and techniques to inform business decisions.
- Creates advanced data mining architectures / models / protocols statistical reporting and data analysis methodologies to identify trends in structured and unstructured data sets.
- Extracts transforms and loads data from dissimilar sources from across the client for their machine learning feature engineering.
- Applies data science/ machine learning /artificial intelligence methods to develop defensible and reproducible predictive or optimization models that involve multiple facets and iterations in algorithm development.
- Wrangles and prepares data as input of machine learning model development and feature engineering.
- Writes and documents reusable python functions and modular python code for data science.
- Assesses business implications associated with modeling assumptions inputs methodologies technical implementation analytic procedures and processes and advanced data analysis.
- Works with sponsor departments and company subject matter experts to understand application and potential of data science solutions that create value.
- Presents findings and makes recommendations to senior management.
- Acts as peer reviewer of complex models.
Qualifications
Minimum Education:
- Bachelors Degree in Data Science Machine Learning Computer Science Physics Econometrics or Economics Engineering Mathematics Applied Sciences Statistics or equivalent field.
Desired Education:
- Doctoral Degree or higher in Data Science Machine Learning Computer Science Physics Econometrics or Economics Engineering Mathematics Applied Sciences Statistics or equivalent field.
- Minimum Work Experience:
- 6 years in data science (or no experience if possess Doctoral Degree or higher as described above).
- Desired Work Experience:
- Relevant industry (electric or gas utility renewable energy analytics consulting etc.) experience
- Knowledge Skills Abilities and (Technical) Competencies:
- Active participation in the external data science/artificial intelligence/machine learning community of practice as demonstrated through volunteering in professional organizations for the advancement of the field presentations in conferences or publications to disseminate data science knowledge and topics or similar activities.
- Competency with data science standards and processes (model evaluation optimization feature engineering etc.) along with best practices to implement them.
- Knowledge of industry trends and current issues in jobrelated area of responsibility as demonstrated through peer reviewed journal publications conference presentations open source contributions or similar activities.
- Competency with commonly used data science and/or operations research programming languages packages and tools for building data science/machine learning models and algorithms.
- Proficiency in explaining in breadth and depth technical concepts including but not limited to statistical inference machine learning algorithms software engineering model deployment pipelines.
- Mastery in clearly communicating complex technical details and insights to colleagues and stakeholders.
- Mastery of the mathematical and statistical fields that underpin data science.
- Ability to develop coach teach and/or mentor others to meet both their career goals and the organization goals.
TekWissen Group is an equal opportunity employer supporting workforce diversity.
Employment Type
Full Time
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