Senior Data Scientist Applied Auto Ml at Urbint

100% Remote - Hiring in the US  and Canada only
At Urbint, our mission is to make communities more resilient. We do this by pairing external data with artificial intelligence to identify areas of high risk and prevent catastrophic loss for utilities and infrastructure operators across the country. We are a team of close-knit engineers, entrepreneurs, and data geeks who obsess over problem-solving, new technologies, and making a positive impact in our communities.
We encourage people from underrepresented groups to apply.
Job Summary 
At Urbint, the machine learning team does not work on making consumers spend more or on maximizing clicks. That is all fine; we work on reducing carbon emissions, reducing infrastructure risk and avoiding fatalities.  We find meaning and excitement solving these problems, and we hope you do, too.
We are looking for a Senior Data Scientist to join our high visibility, high impact Machine Learning team to help with this mission. The ML team collaborates with a diverse, broader-mission team to deliver value for our customers.  Members of the Machine Learning team have the option to major/minor in areas from a large data science specialization spectrum: Technical Product Management, People Management, Data Story-Telling,  Applied ML, ML Research, AutoML (Algo/Performance)  and MLOps (DE, SRE). This is a great role for someone who enjoys variety and is also looking to expand their skill set in a structured fashion.
What You’ll Do
You will major in Applied ML (customer-facing) and minor in AutoML, focused on delivering value to customers. 
You will translate business problems into data science problems, and develop solution frameworks (for repeatability/scaling) with focus on speed to value.
You will own key portions of OKRs that help maximize team productivity. 
You will have strong communication and organizational skills.

You will convey complex ideas & trade-off decisions to business stakeholders. 
You will provide guidance to your team on task level prioritization and cross team coordination.
You may support other teams during ideation with customers. 

Overall, you will be responsible for building ML products that deliver measurable business value for customers.
Who You Are
3+ years of experience in data science/machine learning roles. 
Experience solving concrete, real-world machine learning problems.
Well-versed in Python or R (and willing to continue to learn the Python ecosystem).
Comfortable writing production-ready code.
Demonstrated problem-solving skills and experience maximizing team productivity.
Experience leveraging AutoML technologies.
Up to date with what’s under the hood of some of the advanced ML tools available.
Nice to Have
Experience with startup or Agile environments.
Experience building AutoML tools.
Track record of creating excellent slack emojis and memes.
Benefits
Mission Driven - Some companies use AI to serve better digital ads and trade stocks, we seek to make our communities safer and more resilient
Top Compensation - Competitive compensation package
We are 100% Distributed - work from almost anywhere 
Distributed work monthly stipend
Office Space Stipend for co-working space expenses
Wellness reimbursement
Educational Allowance
Weekly lunch stipend
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Urbint's Core Values
Passionate about customers: We strive to deliver sustainable value and exceed expectations, and we’re not satisfied until our customers are raving fans.
Be decisive: We make timely, informed, and pragmatic decisions to keep the organization moving forward.
Build trust: Our values are the building blocks to trust. As we live them, we grow and build lasting relationships.
Focus on impact: We measure and strive to continuously improve our real-world impact.
Be tenacious: We are agile in our approach to addressing challenges but firm in our beliefs.
Win together: We efficiently leverage our diverse skills and perspectives for one another, united by our shared vision.
We're an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.