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