Belcan
Senior Development Operations Engineer (Data Science)
Location: Normal, IL
Zip Code: 61761
Duration: 12 Months
Qualifications
8+ years of experience in applied ML or data science, including 3+ years in a senior or staff-level role and devops experience.
Expert proficiency in Python for ML development (Good to have: Golang for backend integration).
Proven experience deploying traditional ML models to production with measurable business impact.
Strong knowledge of ML frameworks (Scikit-learn, XGBoost, LightGBM) and data libraries (Pandas, NumPy, Statsmodels).
Hands‑on MLOps experience with tools like MLflow (preferred), Databricks (preferred), Kubeflow, Vertex AI Pipelines, or AWS SageMaker Pipelines.
Experience with model monitoring, drift detection, and automated retraining strategies.
Strong database skills (SQL and NoSQL).
Master's degree or PhD is mandatory.
Preferred
Exposure to retrieval‑augmented generation (RAG) pipelines and vector databases.
Time‑series analysis and anomaly detection experience.
Cloud deployment expertise (AWS, Azure, GCP).
Familiarity with distributed computing frameworks (Spark, Ray).
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Zip Code: 61761
Duration: 12 Months
Qualifications
8+ years of experience in applied ML or data science, including 3+ years in a senior or staff-level role and devops experience.
Expert proficiency in Python for ML development (Good to have: Golang for backend integration).
Proven experience deploying traditional ML models to production with measurable business impact.
Strong knowledge of ML frameworks (Scikit-learn, XGBoost, LightGBM) and data libraries (Pandas, NumPy, Statsmodels).
Hands‑on MLOps experience with tools like MLflow (preferred), Databricks (preferred), Kubeflow, Vertex AI Pipelines, or AWS SageMaker Pipelines.
Experience with model monitoring, drift detection, and automated retraining strategies.
Strong database skills (SQL and NoSQL).
Master's degree or PhD is mandatory.
Preferred
Exposure to retrieval‑augmented generation (RAG) pipelines and vector databases.
Time‑series analysis and anomaly detection experience.
Cloud deployment expertise (AWS, Azure, GCP).
Familiarity with distributed computing frameworks (Spark, Ray).
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