Data Scientist — AI​/ML Engineering & Machine Learning Modeling

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.

• 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 (Big Query, Vertex AI, Cloud Run, S3, Lambda, Sage Maker, etc.).
• Implement CI/CD, automated testing, and monitoring for ML/data projects (Git Hub Actions, Cloud Build, Code Build/Code Pipeline).
• 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.

• 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/Light
  
  GBM, and a deep learning framework (PyTorch or Tensor Flow).
• Hands‑on experience building GenAI/LLM applications and agentic workflows.
• Practical experience building reliable data pipelines and ensuring data quality/lineage on GCP (Big Query).
• CI/CD experience for ML/data projects (e.g., Git Hub Actions, Cloud Build, AWS Code Build/Code Pipeline, etc).
• Practical experience building internal dashboards/apps with Streamlit and/or Plotly Dash.
• Cloud experience with GCP (Big Query, Vertex AI, Cloud Run, Gemini Enterprise) and AWS (S3, Lambda, ECS, Sage Maker).
• 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.

• 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.

• 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

• 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.