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SalaryWe’re Thalo Labs, a NYC-based company on a mission to transform the built environment into a powerful tool for fighting climate change. Where others see buildings as part of the problem, we see an incredible opportunity to leverage existing infrastructure to not only accelerate drawdown, but to transform the built environment from one of the biggest emitters to a carbon sink.
Our team has built self-driving cars at Waymo, worked on satellite imagery at Google, designed systems for John Deere, developed space missions for NASA, engineered bikes for Peloton, led manufacturing design for Boom Supersonic jets, and more. We are united by our shared goal of making products that help us decarbonize today and accelerate drawdown globally tomorrow.
We are seeking an experienced Data Scientist to join our team to drive development of data products across our entire business. At Thalo, we are generating emissions data that no one in the world has seen before. If the opportunity to actually get your hands dirty in the business of decarbonization by unraveling trends and opportunities excites you, read on!
As our first Data Scientist hire, you will be responsible for managing and analyzing large timeseries real world datasets, developing statistical models and algorithms, and providing insights to improve business outcomes and growth. The ideal candidate has strong attention to detail and is highly organized, creative, motivated, and passionate about achieving results. You will be one of the forces behind Thalo’s mission to measure and reduce scope 1 emissions through deep understanding of our data.
What you'll be doing:
- Mining, analyzing, interpreting, displaying, and charecterizing our “first of its kind” time series data to connect the dots that enable decarbonization
- Develop algorithms, tools, and pipelines to automate decarbonization opportunity identification for both Thalo internally and our customers externally
- Create stunning, highly actionable data visualizations and reports to communicate findings and insights effectively
- Develop and refine Thalo’s core decarbonization metrics. We are on a mission to do this with first of its kind data so what we do today is likely to be the gold standard in the industry tomorrow.
- Identify new data sources that Thalo’s data collection systems can integrate and iterate into our data set
Job Requirements:
- Above all, be curious and creative with a strong statistical and visualization background
- M.S. or higher in quantitative discipline such as math, statistics or data science
- Seven years or more experience designing, conducting, analyzing, and interpreting data experiments and/or investigations
- Extensive demonstrated experience with creative data visualization and display, ideally with combustion processes and/or fluid dynamics
- Demonstrated experience analyzing data using Python, Matlab, or similar
Nice to haves:
- Background analyzing, tuning, and/or optimizing gas turbine combustion, boiler combustion, or similar
- Experience with time series databases such as InfluxDB or TimescaleDB
- Experience with Docker, Linux, Shell, Git, CICD, logging, and software development best practices
- Experience with temporal prediction, forecasting, or forward modeling
Target compensation for this role at our current stage is between $130,000 and $180,000 depending on level and experience, plus generous equity option grants at the ground floor.
Perks and Benefits:
- Health, dental and vision available
- Unlimited PTO for exempt (salaried) employees
- Falafel Fridays
- Weekly happy hours
- Quarterly team off-sites
- Stocked pantry
Commitment to Diversity, Equity, and Inclusion:
Thalo Labs is committed to diversity and building an equitable and inclusive environment for people of all backgrounds and experiences. We think that a diverse team is critical to Thalo's success. We especially encourage members of traditionally underrepresented communities to apply, including women, people of color, LGBTQ+ people, veterans, and people with disabilities.
Don’t worry if you don’t tick every box, we still would like to hear from you. We are building a diverse and balanced team that complements each other while covering the critical skills and experience.
