Data Scientist with Machine Learning Engineer

Data Scientist with Machine Learning Engineer 1 week ago Be among the first 25 applicants Key Responsibilities Explore, clean, and analyze structured and unstructured datasets. Apply statistical techniques to generate insights and support business decisions. Develop predictive models using regression, classification, clustering, NLP, or time‑series methods.

Conduct hypothesis testing, A/B experiments, and exploratory data analysis (EDA). Machine Learning Engineering Build, train, and fine‑tune ML models using frameworks such as TensorFlow, PyTorch, Scikit‑learn. Develop and maintain end‑to‑end ML pipelines, including feature engineering, model training, evaluation, and versioning.

Deploy ML models into production using MLOps pipelines and tools like MLflow, Kubeflow, SageMaker, or Vertex AI. Implement monitoring, retraining strategies, and improve model performance. Optimize models for scalability, latency, and resource efficiency.

Must-Have Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, AI/ML, or related field. 3–7+ years of experience as a Data Scientist, ML Engineer, or similar role. Strong programming skills in Python (NumPy, Pandas, Scikit‑learn, Matplotlib, etc.). Experience with ML frameworks (TensorFlow, PyTorch).

Strong understanding of machine learning algorithms, statistics, and data modeling. Experience deploying models in production (Docker, APIs, cloud deployment). Knowledge of SQL and experience with relational and NoSQL databases.

Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, DVC). Seniority level Entry level Employment type Full-time Job function Engineering and Information Technology Industries IT Services and IT Consulting #J-18808-Ljbffr