Data Scientist; Python, Power BI, Databricks, SQL, data modeling, R, Javascript, MondoDB

• Full-time

As a Data Scientist,you will join a client team leveraging petabyte-scale datasets for advanced analytics and model building to enable intelligent, automated equipment and improved decisions by farmers. The client team partners with product managers and data engineers to design, scale, and deliver full-stack data science solutions. You will join a passionate team making a difference by applying innovative technology to solve some of the world's biggest problems.

Responsibilities

• Communicate with impact your findings and methodologies to stakeholders with a variety of backgrounds.
• Work with high-resolution machine and agronomic data in the development and testing of predictive models.
• Develop and deliver production-ready machine learning approaches to yield insights and recommendations from precision agriculture data
• Define, quantify, and analyze Key Performance Indicators that define successful customer outcomes.
• Work closely with the Data Engineering teams to ensure data is stored efficiently and can support the required analytics.

• Demonstrated competency in developing production-ready models in an Object-Oriented program language such as Python.
• Demonstrated competency in using data-access technologies such as SQL, Spark, Databricks, Big Query, Mongo
  
  DB, etc.
• Experience with Visualization tools such as Tableau, Power
  
  BI, Data Studio, etc.
• Experience with Data Modeling techniques such as Normalization, data quality, and coverage assessment, attribute analysis, performance management, etc.
• Experience building machine learning models such as Regression, supervised learning, unsupervised learning, probabilistic inference, natural language modeling, etc.
• Excellent communication skills. Able to effectively lead meetings, document work for reproduction, write persuasively, communicate proofs-of-concept, and effectively take notes.

Additional Qualifications

• Examples of professional work such as publications, patents, a portfolio of relevant project work, etc.
• Familiarity with Distributed Datasets
• Experienced with a variety of data structures such as time series, geo-tagged, text, structured, and unstructured.
• Experience with simulations such as Monte Carlo simulation, Gibbs sampling, etc.
• Experience with model validation, measuring model bias, measuring model drift, etc.
• Experience collaborating with stakeholders from disciplines such as Product, Sales, Finance, etc.
• Ability to communicate complex analytical insights in a manner thatisunderstandable by non - technical audiences.

Salary: $55.00–$58.00 + Bonus + Relocation

All your information will be kept confidential according to EEO guidelines.