Data Scientist, Ag Tech
WHO WE ARE & WHAT WE DO
Founded by global technology pioneer, Larry Ellison and esteemed physician and author, Dr. David Agus, Sensei Ag is a market-changing AgTech company on a journey to improve human nutrition. Our greenhouse farms align technology with the environment to protect and preserve natural resources, while optimizing how we grow food. Merging agriculture and innovation to achieve sustainable farming practices allows us to grow high-quality, delicious produce year-round.
WHERE IS THIS JOB LOCATED?
This is a US REMOTE position.
COMPENSATION
$110,000 - $170,000 / year, Exempt
BENEFITS WE OFFER
- Comprehensive Medical, Dental & Vision Plans
- Prescription Drug Benefits, Employee Assistance Program (EAP) & Employee Wellness
- HSA/FSA
- Basic Life and AD&D & Short and Long-Term Disability
- Paid-Time Off and Travel Assistance Program
- 401K
NOTE: Residents of Hawaii, receive a Comprehensive Healthcare Bundle different from US Mainland plans/programs.
ABOUT THE ROLE
The Data Insights team aims to create a data-driven culture by delivering strong data and promoting smart data usage to uncover insights and inform decisions. We're on the lookout for someone who loves digging through big data to find valuable insights and can share those findings in a clear and relatable way for others. The perfect candidate is eager to mentor others and has a strong interest in developing sustainable agriculture solutions while boosting the access to tasty and nutritious fruits and veggies.
WHAT YOU WILL DO
- Collaborate with company stakeholders to figure out how data can help improve systems or uncover new insights.
- Stay updated on data science techniques and recommend the best ones for specific needs or knowledge gaps.
- Collaborate with experimental teams to create strong and effective experimental designs.
- Create new methods for machine learning.
- Look into existing literature and evaluate the current tech landscape for various applications.
- Work with data engineers to encode algorithms into robust pipelines for routine use.
- Create tools that showcase and interact with data.
WHAT SKILLS DO I NEED TO APPLY?
- You have at least THREE (3) years of working experience using models and algorithms in a business setting WITH a PhD in Data Science, Statistics, Computer Science or related field. Or, you have at least FIVE (5) years experience WITH a MS in a related field.
- Experience in using and implementing machine learning techniques, especially in real-world settings (regression, neural networks, and clustering.)
- Great at communicating both verbally and visually, especially when it comes to presenting data insights in a clear and engaging way.
- Skill in finding data on your own, identifying issues, and experimenting with solutions in modeling and optimization.
- Expert in scripting languages like Python or Julia.
- Expert at extracting data via query languages and from object storage buckets.
- Solid experience in reviewing literature and pulling together key insights.
- Teaming with folks from different departments to understand challenges and data sources.
- Partner with software engineers to keep data sources strong and build the infrastructure we need for regular model use.
- Guide and train others in machine learning.
Bonus points if you have...
- Agricultural modeling.
- Familiarity with data pipelines, ELT tools, and automating jobs.
- Skilled in analytical visualization tools like PowerBI or Tableau.
- Oracle cloud environment.
- Knowledge of data warehouse technologies such as Snowflake, Big Query, Spark, and Parquet.
WHY YOU SHOULD JOIN US
Sensei Ag is expanding and seeking highly skilled individuals to be part of our team. Experience a dynamic and collaborative work culture as we revolutionize health and the future of food. We are looking for individuals who are intelligent, yet humble, dedicated and genuine, with grit and lots of it! Become a part of our team today!
This job description is not intended to be an exhaustive list of all duties, responsibilities or qualifications associated with the job. Other duties may be assigned.
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