Job Description
Job Description Job Title: Senior Development Operations Engineer (Data Science)
Location: Normal, IL
Zip Code: 61761
Duration:12 Months
Pay Rate: $ 72.59/hr
Keyword's: #Normaljobs; #OperationsEngineerjobs.
Start Date: Immediate
Job Description: Key Responsibilities
- ML Technical Leadership - Define ML architecture, best practices, and performance standards for enterprise-scale solutions.
- End-to-End Model Development - Lead the full lifecycle from data preprocessing and feature engineering to training, validation, deployment, and monitoring.
- Traditional ML Expertise - Apply algorithms such as regression, tree-based models, SVMs, clustering, and forecasting to solve high-impact problems ,feature engineering and hyper parameter tuning.
- Programming & Integration - Build scalable ML pipelines and APIs in Python (primary) and Golang (for backend services).
- MLOps Implementation - Design and manage CI/CD pipelines for ML, including automated retraining, model versioning, monitoring, and rollback strategies.
- Statistical Analysis - Apply hypothesis testing, Bayesian methods, and model interpretability techniques to ensure reliable insights.
- Cross-Functional Collaboration - Partner with engineering, analytics, and product teams to align technical solutions with business objectives.
Devops Experience - Experience with database setup, databricks, aws, CI/CD, DevOps/MLOps, vectorDBs, GraphDB
Qualifications Must Have:
- 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).
- Masters 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).
Soft Skills
- Strategic problem-solver with the ability to align AI solutions to business goals.
- Excellent communicator across technical and non-technical stakeholders.
Belcan is an equal opportunity employer. Your application and candidacy will not be considered based on race, colour, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
Job Tags
Local area, Immediate start,