neteffects
Data Scientist — AI/ML Engineering & Machine Learning Modeling
neteffects, Saint Louis, Missouri, United States, 63146
Total Hours 1,032.00
Description: We’re hiring a hands-on Data Scientist with strong AI/ML engineering skills to help design and build AI/ML solutions across cloud platforms. You’ll work with business and engineering partners to translate business problems into measurable, scalable AI/ML services — including GenAI agents, production ML models, and lightweight internal apps.
What you’ll do
Partner with business and engineering teams to translate problems into measurable AI/ML solutions and success metrics.
Design, train, validate, and deploy models for classification, regression, recommendation, and time-series forecasting; pick algorithms, features, and evaluation strategies that match business goals.
Develop and evaluate GenAI agent applications using frameworks like Langchain and Google ADK, leveraging techniques such as RAG, prompt engineering, and vector DB integration.
Build and operate reliable data pipelines and model inference endpoints across GCP and AWS (BigQuery, Vertex AI, Cloud Run, S3, Lambda, SageMaker, etc.).
Implement CI/CD, automated testing, and monitoring for ML/data projects (GitHub Actions, Cloud Build, CodeBuild/CodePipeline).
Create lightweight dashboards and internal apps (Streamlit, Plotly Dash) to deliver models and insights to stakeholders.
Write clear model documentation: problem formulation, modeling approach, validation, data needs, and deployment steps.
Advocate for coding best practices, reproducibility, and shared documentation across a global data science organization.
Required qualifications
Master’s + 1+ years, or a PhD in Data Science, Computer Science, Applied Math/Statistics, Econometrics, or related quantitative field.
Strong Python and SQL skills; experience with scikit-learn, XGBoost/LightGBM, and a deep learning framework (PyTorch or TensorFlow).
Hands‑on experience building GenAI/LLM applications and agentic workflows.
Practical experience building reliable data pipelines and ensuring data quality/lineage on GCP (BigQuery).
CI/CD experience for ML/data projects (e.g., GitHub Actions, Cloud Build, AWS CodeBuild/CodePipeline, etc).
Practical experience building internal dashboards/apps with Streamlit and/or Plotly Dash.
Cloud experience with GCP (BigQuery, Vertex AI, Cloud Run, Gemini Enterprise) and AWS (S3, Lambda, ECS, SageMaker).
Solid comprehension of the mechanisms behind widely used AI/ML algorithms — including their intuition, assumptions, statistical theory, computational complexity, strengths/weaknesses, and when to use each.
Preferred qualifications
Security and compliance best practices: IAM, secrets management, VPC/networking.
Experience building APIs for model/agent inference.
Containerization & orchestration.
Workflow orchestration.
Background in causal inference, statistics, or econometrics.
A/B testing and experimentation design.
About the team
Global Data Science organization: 70+ data scientists partnering with business teams across Bayer Crop Science.
AI/ML Team: 26+ cross‑functional members growing rapidly.
Typical project teams: small, autonomous groups (2–3 people) that collaborate closely with internal clients and engineers.
Is travel required for this position? No
Will the work location for this assignment be office based, remote, or hybrid? Remote
Worker Shift Start Time AM - 09:00 AM
Benefits (employee contribution)
Health insurance
Health savings account
Dental insurance
Vision insurance
Flexible spending accounts
Life insurance
Retirement plan
All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Rate of pay within the stated range will depend on the qualification of the applicant.
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Description: We’re hiring a hands-on Data Scientist with strong AI/ML engineering skills to help design and build AI/ML solutions across cloud platforms. You’ll work with business and engineering partners to translate business problems into measurable, scalable AI/ML services — including GenAI agents, production ML models, and lightweight internal apps.
What you’ll do
Partner with business and engineering teams to translate problems into measurable AI/ML solutions and success metrics.
Design, train, validate, and deploy models for classification, regression, recommendation, and time-series forecasting; pick algorithms, features, and evaluation strategies that match business goals.
Develop and evaluate GenAI agent applications using frameworks like Langchain and Google ADK, leveraging techniques such as RAG, prompt engineering, and vector DB integration.
Build and operate reliable data pipelines and model inference endpoints across GCP and AWS (BigQuery, Vertex AI, Cloud Run, S3, Lambda, SageMaker, etc.).
Implement CI/CD, automated testing, and monitoring for ML/data projects (GitHub Actions, Cloud Build, CodeBuild/CodePipeline).
Create lightweight dashboards and internal apps (Streamlit, Plotly Dash) to deliver models and insights to stakeholders.
Write clear model documentation: problem formulation, modeling approach, validation, data needs, and deployment steps.
Advocate for coding best practices, reproducibility, and shared documentation across a global data science organization.
Required qualifications
Master’s + 1+ years, or a PhD in Data Science, Computer Science, Applied Math/Statistics, Econometrics, or related quantitative field.
Strong Python and SQL skills; experience with scikit-learn, XGBoost/LightGBM, and a deep learning framework (PyTorch or TensorFlow).
Hands‑on experience building GenAI/LLM applications and agentic workflows.
Practical experience building reliable data pipelines and ensuring data quality/lineage on GCP (BigQuery).
CI/CD experience for ML/data projects (e.g., GitHub Actions, Cloud Build, AWS CodeBuild/CodePipeline, etc).
Practical experience building internal dashboards/apps with Streamlit and/or Plotly Dash.
Cloud experience with GCP (BigQuery, Vertex AI, Cloud Run, Gemini Enterprise) and AWS (S3, Lambda, ECS, SageMaker).
Solid comprehension of the mechanisms behind widely used AI/ML algorithms — including their intuition, assumptions, statistical theory, computational complexity, strengths/weaknesses, and when to use each.
Preferred qualifications
Security and compliance best practices: IAM, secrets management, VPC/networking.
Experience building APIs for model/agent inference.
Containerization & orchestration.
Workflow orchestration.
Background in causal inference, statistics, or econometrics.
A/B testing and experimentation design.
About the team
Global Data Science organization: 70+ data scientists partnering with business teams across Bayer Crop Science.
AI/ML Team: 26+ cross‑functional members growing rapidly.
Typical project teams: small, autonomous groups (2–3 people) that collaborate closely with internal clients and engineers.
Is travel required for this position? No
Will the work location for this assignment be office based, remote, or hybrid? Remote
Worker Shift Start Time AM - 09:00 AM
Benefits (employee contribution)
Health insurance
Health savings account
Dental insurance
Vision insurance
Flexible spending accounts
Life insurance
Retirement plan
All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Rate of pay within the stated range will depend on the qualification of the applicant.
#J-18808-Ljbffr