- Company Name
- Scope AT Limited
- Job Title
- Machine Learning Engineer/Data Scientist - ML, Data Science, Python, AI, Engineer, ML Ops
- Job Description
-
**Job Title**
Machine Learning Engineer / Data Scientist
**Role Summary**
Design, develop, and deploy machine‑learning models for a global payments platform. Engineer and maintain end‑to‑end ML pipelines, integrate models into web services, and ensure robust CI/CD, DevOps, and ML‑Ops practices.
**Expectations**
- Deliver production‑grade models that meet accuracy, latency, and reliability targets.
- Collaborate with product, data, and engineering teams to translate business problems into data solutions.
- Maintain knowledge of emerging AI/ML technologies and industry best practices.
**Key Responsibilities**
- Build and optimize predictive models using Python and relevant libraries (pandas, NumPy, scikit‑learn, PyTorch, TensorFlow).
- Develop and maintain data ingestion pipelines, feature stores, and model serving endpoints (RESTful APIs, gRPC).
- Implement CI/CD workflows for model training, validation, and deployment (Git, Jenkins, Azure Pipelines, GitHub Actions).
- Manage model versioning, monitoring, and logging (MLflow, Prometheus, Grafana).
- Perform unit and integration testing, model explainability (SHAP, LIME), and bias audit.
- Automate workflow orchestration (Airflow, Prefect) and resource provisioning on AWS or Databricks.
- Participate in code reviews, knowledge sharing, and continuous improvement initiatives.
**Required Skills**
- Strong Python programming and data‑science library experience.
- Proven experience in ML Ops: model lifecycle management, CI/CD, DevOps.
- Familiarity with cloud platforms (AWS, Databricks) and containerization (Docker, Kubernetes).
- Ability to design web servers/APIs for model deployment.
- Solid understanding of data engineering principles, ETL, and feature engineering.
- Knowledge of unit testing, model explainability, and monitoring tools.
- Good communication and collaboration skills in cross‑functional teams.
**Required Education & Certifications**
- Bachelor’s (or higher) degree in Computer Science, Statistics, Engineering, or related field.
- Preferred: Master’s degree in Data Science, Machine Learning, or Business Analytics.
- Relevant certifications: AWS Certified Machine Learning – Specialty, Google Cloud Professional Data Engineer, or TensorFlow Developer Certificate.