Data Scientist

Job Title:- Data Scientist

Location:- Indianapolis, IN

Duration:- 12+ months

Rate:- DOE

Job Description

The candidate must have experience and fundamental knowledge in machine learning, experience in deploying models, and programming skills to develop and deliver Client solutions in an industry setting.

Responsibilities: Partner with R&D scientists to develop and prototype rigorous machine learning solutions aligned to project needs.

Design and implement scalable data pipelines for processing high-complexity datasets such as high-throughput bioassays or large-scale agriculture datasets

Partner with data scientists, data engineers, and production teams to deploy and maintain data products at scale

Communicate and train research partners on models and products to facilitate data-driven decisions

Communicate insights derived from complex data analysis into simple conclusions that empower leadership to drive action; communicate results in internal and external forums; and contribute to scientific articles as needed

Steward data product life cycle and partner with other scientists to continuously improve underlying models and optimize data architecture

Stay abreast of emerging technologies in big data, machine learning, and agriculture tech and advocate for their adoption where beneficial

Required Qualifications

7-8 Years of strong expertise in R or Python programming languages and their application to data wrangling, machine learning (e.g., TensorFlow, PyTorch), and data visualization

Experience and fundamental understanding of machine learning techniques (e.g., logistic regression, random forest, XGBoost, SVMs, K-means, neural networks)

Solid understanding of variable selection; dimensionality reduction; model diagnostics; and model training, testing, and validation

Experience deploying machine learning models in production (e.g., CI/CD pipeline development; containerization using tools such as docker, podman, or Kubernetes; Git)

Ability to work both independently and within a multidisciplinary team environment to provide innovative solutions

Ability to successfully collaborate with colleagues from diverse technical backgrounds which includes excellent communication, interpersonal, verbal, and written skills

Strong critical thinking and problem-solving skills, flexibility, and willingness to learn

Preferred Qualifications:

Familiarity with modeling biological, cellular, or ecological data; molecular biology or biochemistry concepts; or data science in agriculture

Proven experience as a machine learning engineering or similar role with a strong focus on machine learning deployment and data pipeline construction

Familiarity with artificial intelligence or generative AI techniques

Experience in big data technologies (e.g., Hadoop, Spark) and database management systems (e.g., SQL, NoSQL)

Experience with AWS

Experience consulting on scientific projects or working within a scientific team