Analytics Engineer at EquipmentShare

4 weeks ago

Columbia, United States Serendeputy LLC Full time

Remote; Columbia, MO; Denver; Chicago; Kansas City

EquipmentShare

Get the newest equipment, track your entire fleet and put your assets to work when you aren't using them, all with EquipmentShare.

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EquipmentShare is Hiring an Analytics Engineer EquipmentShare is searching for an Analytics Engineer to join our team. This position is fully remote. What You’ll Do as an Analytics Engineer Despite having been fundamentally altered by earlier industrial revolutions, the construction industry has hardly budged with the computer revolution. In fact, since 1970, labor productivity in the US construction industry has actually declined, despite it more than doubling in the rest of the economy. This has contributed to housing shortages and the parlous state of infrastructure in some places, and is sanding the gears of carbon reduction efforts. We think the industry is ripe for change, and we’re pushing the leading edge of that change with our next generationT3 Platform , the OS for Construction. Through T3, we help contractors to coordinate humans and (increasingly smarter) machines to build more effectively. As an Analytics Engineer in our small and quickly growing team, you will play a major role in this effort. In particular, you will: Establish sound pipelines and clear table structures for a wide variety of metrics used by both the business analytics and data science / ML engineering parts of the organization Work closely with the rest of the Data Science & Analytics Platform team to enable cutting edge algorithms, causal inference and analytics within a fast-moving environment, while adhering to industry best practices in terms of data access, security, traceability, etc About You as an Analytics Engineer Our mission is to change an entire industry, so we only hire people inspired by the goal and up for the challenge. In turn, our employees have every opportunity to grow with us, achieve personal and professional success and enjoy making a tangible difference in a crucial industry for human welfare. Minimum Qualifications for an Analytics Engineer Undergraduate degree, or equivalent practical experience, in computer science, machine learning, software engineering, statistics or related field 2+ years working on technology-powered products as either a data platform engineer, data engineer, ML engineer, analytics engineer or a closely related role Experience with data modeling: specifically the creation of dimensional models and fact tables (Data Vault experience not necessary but would be a plus) Demonstrated understanding of the techniques and methods of modern product development Demonstrated understanding of business analytics Strong cross-functional communication skills Must be qualified to work in the United States or the United Kingdom - we are not sponsoring any candidates at this time Why We’re a Better Place to Work Competitive compensation packages 401 (k) and company match Health insurance and medical coverage benefits Unlimited paid time off Generous paid parental leave Volunteering and local charity initiatives that help you nurture and grow the communities you call home Opportunities for career and professional development with conferences, events, seminars, continued education State of the art onsite gym (Corporate HQ)/Gym stipend for remote employees Since our incorporation in 2015, we’ve had incredible growth — and we’re not stopping anytime soon. Ready to invest in our mission, invest in yourself and discover a better place to work? Then, we’d love to meet you. At EquipmentShare, it’s more than just a job — it’s a calling. Apply today. EquipmentShare is committed to a diverse and inclusive workplace. EquipmentShare is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.

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