HowGood is an independent research company and SaaS data platform with the worlds largest database on food product sustainability. With more than 90,000 on-farm emissions factors for food ingredients, HowGood helps leading brands, retailers, suppliers and restaurants to measure, manage, and communicate their environmental and social impact.

The data team at HowGood plays a central role in helping our customers decarbonize their supply chains across the food and beverage industry. Carbon accounting and carbon reduction is a critical focus for HowGood, but not our sole focus. We take a holistic look across environmental and social impacts. Our data team’s work is what allows our customers to understand their impacts and enables them to do the hard work of transforming their supply chains.

Our data team is responsible for wrangling and ingesting customer data, and mapping it to our extensive database of ingredients, crops and locations. ETL is a core part of the job. The team also peer reviews teammates’ functions, scripts and outputs; designs and produces custom reports for customers; and contributes to process improvements big and small such as automating scripted processes, systematizing data ingestion steps using data tooling, and data science projects that solve tricky problems. The data team collaborates with the rest of Research and the Customer Success and Engineering teams. We seek a candidate who has the right technical chops, good communication skills, and comfort participating in a fast moving, business goal driven environment.

Applicants should have an interest and excitement in integrating different data structures and formats, improving and standardizing processes, and a passion for sustainability and regenerative agriculture. HowGood’s data complexity is derived from our database structure and the variety of sources we use. A core part of HowGood’s strength is in the data team, including the flexibility required to map customer data to our database so our customers can see and understand the impacts their products are having on carbon, water, biodiversity, working conditions, and more. The right candidate will be excited by the challenge and ready to creatively contribute solutions.

This is a US-based role. Applications without a cover letter won’t be considered.
Qualifications:

• A minimum of 2 years of relevant data work experience after graduation
• Experience and comfort working on a remote team
• Analytical and problem-solving skills
• Ability to reprioritize as needed and meet deadlines
• Ability to work independently and in collaboration with different teams
• Clear judgment based on priorities and context
• Attention to the right details
• Ability to overlap East coast hours

Required Skills:

• Strong mathematics skills (Masters level applied statistics preferred)
• Proficiency in Python, SQL, and spreadsheets
• High degree of comfort with data management, ETL techniques, and data ingestion
• Experience with QA/QC testing and data troubleshooting
• AWS Glue, Step, S3, Admin, or similar data tooling experience a plus
• Classification, NLP, statistical machine learning modeling experience a plus
• Experience with Python Regex library a plus
• Experience with Pyspark a plus
• Experience with Mac OS and Google suite