Head Data Scientist

Head Data Scientist

Remote

Louisville, Colorado, United States

Delivery

Full time

ESC-T4.2/T5.1

Description

Resource Innovations is seeking a Head Data Scientist to join our growing team preferably in Louisville, Colorado (USA), or Toronto, Ontario (Canada), however, other locations within the United States or Canada will be considered. As the Head Data Scientist with Resource Innovations, you will be responsible for providing technical oversight and project management, while driving team growth, and team development for the Advisory Services business unit.

This position is responsible for identifying, architecting, and deploying analytical solutions for our utility, software, and energy efficiency delivery teams. As a result, the ideal candidate will have significant experience at the intersection of programming, statistical modeling, and software development. This is a highly collaborative position and the candidate must be self-directed and comfortable supporting the analytical needs of multiple teams, systems, and products.

Specific responsibilities will include supporting: hiring/team growth, team development, processes, and resource planning, as well as project management and delivery of on-time and under budget services.

Candidates with more than 7 years of related work experience are encouraged to apply.

Resource Innovations (RI) is a women-led energy transformation firm focused on impact. Building on our expertise in energy efficiency, we’re constantly expanding our portfolio of clean energy solutions to guide utilities through increasingly complex, connected challenges. Load flexibility. Electrification. Carbon reduction. With every step, we’re leading the charge to power change.

Duties and Responsibilities

• Use knowledge of utility data, organizations and priorities to advise clients on data-driven solutions to operational needs, regulatory mandates, and customer outreach.
• Leverage knowledge of the electricity and gas sector to select appropriate statistical and technical approaches to client challenges.
• Prepare reports, presentations, tools, and proposals explaining technical analytical methods and results to both technical and non-technical audiences.
• Familiarity with the full data science stack, with a focus on machine learning, data visualization and communication of complex results to a variety of audiences
• Write production-level machine learning pipeline code
• Create and provide guidance on solution architectures including integration with Amazon Web Services (AWS) and /or Azure.
• Project manage and/or support teams to deliver high quality analysis while remaining on time and on budget.
• Take initiative to validate and troubleshoot data and statistical models.
• Coach junior staff to develop their data science skills.
• Define hiring needs, and support recruiting, hiring, and onboarding of new team members.
• Lead meetings, conference calls, and email exchanges with clients
• Track energy industry trends and emerging issues
• Other duties as assigned.

Requirements

• A Bachelors degree in a quantitative field is required; a Master’s Degree is strongly preferred.
• A minimum of 7+ years of work experience in one or more of the following disciplines: data science, economics, statistics, public policy with a quantitative focus, or computer science
• Experience performing advanced customer data analytics, including propensity modeling and high frequency consumption data analysis
• Substantial work experience in the energy and utilities sector
• Practical experience in machine learning, applied econometrics and/or statistical program evaluation
• Real world experience scraping and/or munging large data sets
• Significant programming experience using R, Python and SQL to build and deploy regression, classification, and other statistical models.
• Experience building machine learning pipelines.
• Strong written and oral communication skills
• Experience with model selection and validation methods
• Strong data visualization skills
• Understanding of relational databases and basic architectural principles

Preferred Qualifications

• Experience with AWS and/or Azure to deliver data-driven solutions.
• AWS certifications are highly preferred.
• Experience using Tableau or other data visualization software
• Familiar with the use of version control (e.g. git/GitHub)
• Project management experience, including supervising junior staff and tracking budgets and deliverables, preferably in a consulting or client-facing environment.

Benefits

Resource Innovations offers competitive salaries based on candidate’s qualifications. Resource Innovations also offers three weeks paid vacation per year, paid holidays, a 401(k) plan with employee matching funds, a discretionary bonus and an overall comprehensive benefits package.

About Resource Innovations
Resource Innovations (RI) is a women-led energy transformation firm focused on impact. Building on our expertise in energy efficiency, we’re constantly expanding our portfolio of clean energy solutions to guide utilities through increasingly complex, connected challenges. Load flexibility. Electrification. Carbon reduction. With every step, we’re leading the charge to power change.

Resource Innovations is an Equal Opportunity Employer, committed to ensuring equal employment opportunities for all job applicants and employees without regard to race, color, religion, national origin, gender, age, disability, marital status, genetics, protected veteran status, sexual orientation, or any other protected status. In addition to federal law requirements, Resource Innovations complies with applicable state and local laws governing non-discrimination in employment in every location in which the company does work.

The above job description and job requirements are not intended to be all inclusive. Resource Innovations retains the right to make changes or adjustments to job descriptions and/or job requirements at any time without notice.

The compensation range for this exempt position is $120000- $220000. The stated range is based on a good faith estimate of the compensation range for the duties, responsibilities and skills / experience required for the position. Starting pay will be dependent on experience and internal equity. This provided range may exceed this range for well-qualified candidates, especially with industry experience.