What are the responsibilities and job description for the Senior Data Scientist position at Finezi Inc.?
We are seeking two (2) experienced data scientist to join our client as expert members of company’s 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.
Qualifications
Minimum Education :
Bachelor’s 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 job-related 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.
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