Indigo improves grower profitability, environmental sustainability, and consumer health through the use of natural microbiology and digital technologies. Utilizing beneficial plant microbes and agronomic insights, Indigo works with growers to sustainably produce high quality harvests. The company then connects growers and buyers directly to bring these harvests to market. Working across the supply chain, Indigo is forwarding its mission of harnessing nature to help farmers sustainably feed the planet. The company is headquartered in Boston, MA, with additional offices in Memphis, TN, Research Triangle Park, NC, Basel, Switzerland, Sydney, Australia, Buenos Aires, Argentina, and São Paulo, Brazil. http://www.indigoag.com/
The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.
- Analyze raw data: assessing quality, cleansing, structuring for downstream processing
- Clean and prepare unstructured dataset, enabling data ingestion into Data Warehouse.
- Analyze data generated across business units operations (e.g. lab, results, field trials, commercial trials), creating insights for decision-making process and for Marketing material.
- Ensure consistent field data collection and data standardization, aligned with Data Science team requirements
- Collaborate with BI and GioInnovation team to generate reports and dashboards that supports operations and services for clients.
- Work with Data Science team to produce compelling and clear visualizations of agronomic field data and statistical findings.
- Support in system integration processes with internal and third-party systems.
- Good communication skills: Ability to communicate data collection process with data science team
- Curious, perceptive and entrepreneurial: Enjoys new technology
- A Team player – thrives working in cross functional teams throughout the organization.
- Flexible to different types of analysis and different stakeholders (e.g. lab science, field trials, commercial team)
- Fluency in English is required.
- Experience in quantative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
- At least 1 - 2 years' of experience in data analytics or data modeling
- Good understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms
- Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau)
- Advanced Excel Skills
- Experience querying databases
- Experience visualizing and reporting data for stakeholders
- Experience using computer languages for data scrubbing and executing exploratory data analysis (EDA).