Sphera, the former Operational Excellence and Risk Management business of IHS Inc. is a leading global provider of enterprise software and services that enables companies to manage and optimize their environmental, health, safety and sustainability processes. Our software allows customers to automate processes, monitor emissions, ensure regulatory compliance, and track chemical inventory throughout a manufacturing cycle. We were recently spun off by IHS and acquired by Genstar Capital, essentially positioning us as a start-up tech company with $100 million in annual revenue and over 3000 customers in 70+ countries.
At Sphera, it is more than just a job. If you are looking to help change the world and challenge status quo while growing your career, you might find some interesting opportunities to pursue whether for you or to refer a colleague.
As a Data Scientist, you will work with Sphera’s comprehensive data set and create models and algorithms that will be productized into Sphera’s products. You will collaborate with a multi-disciplinary team of engineers and analysts on a wide range of problems. This position will bring analytical rigor and statistical methods to the challenges of helping companies to keep their employees safe, improve their internal business processes, and enhance their decision making through data.
• Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
• Create predictive and prescriptive models that will be productized into Sphera products to provide data driven insights to our customers.
• Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive understanding of Sphera data structures and metrics, advocating for changes where needed for both products development and sales activity.
• Interact cross-functionally with a wide variety of people and teams. Work closely with engineers to identify opportunities for, design, and assess improvements to products.
• Make business recommendations (e.g. cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
• Research and develop analysis, forecasting, and optimization methods to improve the quality of Sphera's products.
• MS degree in a quantitative discipline (e.g., statistics, operations research, bioinformatics, economics, computational biology, computer science, mathematics, physics, electrical engineering, industrial engineering)
• 3-5 years of relevant work experience in data analysis or related field. (e.g., as a statistician / data scientist / computational biologist / bioinformatician).
• Experience with statistical software (e.g., R, Julia, MATLAB, pandas, Alteryx, Knime, etc.) and database and programming languages (e.g., PL/SQL, Transact-SQL, Python, etc.).
• Applied experience with machine learning on large datasets.
• Experience with querying and analyzing Oracle and SQL Server databases.
• Demonstrated effective written and verbal communication skills.
• 5 years of relevant work experience (e.g., as a statistician / computational biologist bioinformatician / data scientist), including deep expertise and experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods. Analytical engagements outside class work while at school can be included.
• Experience articulating business questions and using mathematical techniques to arrive at an answer using available data. Experience translating analysis results into business recommendations.
• Demonstrated skills in selecting the right statistical tools given a data analysis problem.
• Demonstrated leadership and self-direction. Demonstrated willingness to both teach others and learn new techniques.
Sphera is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, age, gender identity, sexual orientation, marital status, parental status, religion, sex, national origin, disability, veteran status and other legally protected characteristics.