Data Scientist, Vegetation Ecology, Remote Sensing & Utility Management - REMOTE

E SOURCE • Buffalo, NY

10d • $95,000 - $145,000 • Remote

About The Position

Are you an experienced data scientist looking to join an industry-leading team? E Source develops groundbreaking data science applications that change the way utilities understand and manage their networks. We tackle challenging projects like optimizing vegetation management strategies and forecasting the impact of severe weather on utility networks. To conduct these projects, we use a combination of machine learning models, inference-based statistics, and remote-sensing applications. Each project or product is collaboratively developed in-house by a data science team of diverse professional backgrounds and domain expertise. Ultimately, our work helps utilities enhance their electric reliability and prepare to adopt and deploy cutting-edge green energy technology. A little about E Source E Source combines industry-leading research, data science, and consulting to help utilities make and implement better data-driven decisions that positively impact their customers, their bottom line, and our planet. Headquartered in Boulder, CO, we have teams across the US and Canada. Learn more at www.esource.com. How you’ll help: Fit and assess predictive models leveraging geospatial data sources in R and/or Python. Explore and analyze client-provided assets and reliability data sets. Collaborate with a broader data science and engineering team to take projects and products from inception to client delivery. You’ll be a full-time member of the E Source Data Science team. Our data science positions appeal to self-starters who welcome and excel in team-based, collaborative projects from conception to end-user handoff, providing an excellent customer experience throughout. The ability to simplify complex analyses into understandable concepts that are applicable to management and operations is highly desired.

Requirements

• Master’s or PhD and multiple years with applied experience in forestry, ecology, vegetation-related remote sensing, statistics, or a similar field.
• Minimum three years conducting data science projects using spatial or time-series data sets in industry or applied research—analytical design, managing schedules, and communicating results to stakeholders.
• Extensive experience fitting and assessing predictive models using regression techniques in R and/or Python.
• Experience conducting all phases of analysis, including data compilation, exploratory data analysis, feature engineering, and deliverable generation (visualizations, reports, output files).
• Experience working as part of a larger data science team, collaborating with technical or nontechnical peers and stakeholders.

Nice To Haves

• Domain expertise using regression techniques (e.g., generalized linear models, generalized linear mixed models, zero-inflated models, regression trees).
• Domain expertise using remotely sensed and satellite data sets.
• Experience using cloud computing infrastructure (e.g., Amazon Web Services) and collaboration version control (e.g., Git).
• Domain expertise in the utilities sector (electric, gas, water).

Responsibilities

• Fit and assess predictive models leveraging geospatial data sources in R and/or Python.
• Explore and analyze client-provided assets and reliability data sets.
• Collaborate with a broader data science and engineering team to take projects and products from inception to client delivery.

Benefits

• Excellent insurance options, including medical, dental, and vision plans; company-paid life insurance; company-paid long- and short-term disability insurance; and medical and dependent-care flexible spending plans.
• A flexible time off (FTO) program where you can take as many paid days off per year as they need, with manager approval, while fulfilling their work obligations and ensuring proper coverage of their responsibilities.
• Flexible schedules, flexible work locations, and a paid parental leave benefit.
• A 401(k)/RRSP plan with a 3% employer match.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 251-500 employees