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Job Location: United States
Data Analyst
Location: Remote
Duration: 12 Months
Description:
Candidates with a background in data analysis are highly desired for this position. The individual will be responsible for working on several projects across our team focused on detecting, flagging, and improving data quality. The position involves working with large geospatial datasets generated by agricultural machinery. The work will include exploratory data analysis (EDA), root cause analysis, data summarization and visualization. This role will also be expected to complete ad hoc requests for descriptive data statistics and communicate across teams to understand data origination, data pipeline, and downstream use-cases. A successful candidate should have the ability to work effectively across functions to complete data wrangling, EDAs, and visualizations/summaries while maintaining a high quality of work. Experience working with geospatial data is preferred but not required. This position is expected to interact with various functions within the company, including data analytics, science, engineering, and product. Attention to detail, intellectual curiosity, and open communication are key for the success in this role.
Required Skills / Experience:
– BA/BS in Applied Math, Statistics/Data Science, Biostatistics, Computer Science, Physics, Agronomy, Engineering or a related quantitative discipline with at least two years of data analytics or data science experience.
– Strong Python coding skills, including competency/experience with core data wrangling and visualization libraries (pandas, geopandas, matplotlib, seaborn) and a willingness to learn new code bases
– Strong technical and code documentation skills (e.g., git)
– Basic-to-intermediate statistics knowledge with the ability to run exploratory data analysis, root cause analysis, and data summarization
– Critical thinker, detail-oriented, and an analytical mindset
– Self-starter as well as able to work as part of a team
– Strong communication skills to solicit information from domain experts and present results back to different audiences.
Desired Skills / Experience:
– Master’s degree in a quantitative analytics field
– Experience with complex data formats, including geospatial data and data of varying quality, as well as physical measurements and sources of error
– Knowledge of agricultural technology especially with regard to row crops
– Curiosity and an open-mind towards unfamiliar data sources and unfamiliar quantitative domains
– Experience with exploratory Big Data discovery through the use of technologies such as Tableau, Hadoop, MapReduce, or Spark
– Background with building dashboards (Dash, Looker) or other reporting tools for metrics and data quality analysis
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