Senior Data Scientist
$150,000–$180,000 year
On-siteSomerville, Massachusetts, United States
Job Summary
Analyze historical spray application data to identify patterns impacting input parameters, rates, mixtures, and environmental conditions. Apply advanced statistical, machine learning, and optimization methodologies to solve complex agricultural challenges and architect the RealCoverage Recommendation Engine. Build tooling for non-technical domain experts, define scalable data quality measures across multimodal labeling pipelines, and collaborate with cross-functional teams to design robust data pipelines. Communicate technical findings and data limitations clearly to internal partners and external collaborators. Located in Somerville, MA with in-person work required; seasonal travel for manufacturing builds.
Required Qualifications
- MS or PhD in Computer Science, Engineering, Statistics, Mathematics, Physics, or related field (or BS with equivalent work experience)
- Proficient using data query languages (SQL/postgreSQL) to quickly build complex yet efficient data queries at scale
- Proficient using Python to build production-quality code
- Proficient in exploratory data analysis (EDA) and data visualization to understand and present trends and their implications for the business
- Background in statistical modeling and analysis, including experience making data-driven decisions from physical sensor data
- Proven experience in the use of the main data-science, analytics, modeling and visualization Python libraries, including machine learning and deep learning
- Strong data-centric ML development, careful data curation, and the ability to quickly develop agricultural domain expertise
- Creative, naturally curious, and willing to take intellectual risks
- Adaptability to different business challenges and data types / sources and to learn and utilize a range of different analytical tools and methodologies
- Analytical problem-solving skills with innovative thinking, while effectively collaborating across diverse teams and managing multiple priorities in a multicultural scientific environment
- Work required to be in-person
- Travel to support AgZen's major manufacturing builds (seasonal) will be required
Desired Qualifications
- Experience with the field of agriculture or related fields such as environmental or life sciences
- Knowledge of interfacial science, crop science and/or fluid dynamics
- Experience with data science based on real-world physical sensors data
- Experience with vision-based ML
- Prior experience in developing data-driven customer facing recommendation system
- Experience creating intuitive data visualization tools that make complex data approachable for non-technical users
- Prior experience in developing machine-learning models relevant to biological or crop protection outcomes
- Advanced scientific Python (NumPy, Pandas, scikit-learn) and hands-on experience with PyTorch and/or TensorFlow, including training and deploying neural networks
- Hands-on experience leveraging generative AI approaches for data exploration, model development, or research acceleration
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