Sr Data Scientist - Indianapolis, IN
Georgia IT Inc
Position - Sr Data Scientist
Location : Indianapolis, IN
Rate - DOE
Start Date - ASAP Project 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
Required Qualifications
Location : Indianapolis, IN
Rate - DOE
Start Date - ASAP Project 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
Vacancy posted 4 days ago
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