Passionate data scientist with a robust background in credit scoring, machine learning, and natural language processing (NLP), aiming to leverage advanced analytics to drive business insights, optimize decision-making processes, and foster innovation in dynamic environments.

• Programming Languages: Python, Java, Shell Scripting
• Machine Learning/MLOps: Scikit-learn, TensorFlow, MLflow, Kubeflow
• Data Engineering: Kedro, Redash, Pandas Profiling, Seaborn, NumPy
• Web Frameworks: FastAPI, Flask
• Cloud Services: AWS (S3, Lambda, EC2, CloudFormation, CloudWatch, RDS, AWS-CLI, EKS, EBS, EFS, ECR, IAM roles and management)
• Version Control: GitHub, GitLab
• Containerization & Orchestration: Docker, Kubernetes/EKS
• CI/CD & Deployment: Terraform, ArgoCD, GitOps
• Project Management: Jira

• Tools/Frameworks: AWS Services, FastAPI, Docker, MLflow, Kubeflow, feast
• What it does: Developed an alternative data-driven credit scoring and configurable decisioning platform for short-tenure loan products. Implemented and deployed multiple machine learning models, establishing fully automated MLOps pipelines for seamless integration and operational efficiency.
• Evaluation of stability: Monitored accuracy, performance metrics, and robustness to data shifts and noise. Successfully processed over 1,000,000 requests with response times consistently under 1 second, serving a user base of 60,000 unique customers over a one-year period.

• Tools/Frameworks: Redash, AWS Services (S3, EC2, RDS, Lambda), Kedro
• What it does: Developed an ETL pipeline for an edutech company to extract over six years of financial report data and integrate it with their ledger software. Built analytics dashboards to provide actionable insights into financial activities.
• Usability: Enabled a 30% increase in user adoption of financial analytics dashboards and reports, leading to a 25% reduction in time spent on data retrieval and analysis.

• Tools/Frameworks: AWS Services (S3, EC2, RDS, Lambda), Kedro
• What it does: Developed an ETL pipeline for an edutech company to extract their 3-year OKR planning data and integrate it with available resources. Implemented semantic keyphrase embedding and graph techniques to resolve hierarchical-based conceptual data mapping and grouping challenges. Built analytics dashboards for actionable insights into KPI and OKR mapping.
• Impact: Enabled a 15% increase in user adoption of KPI and OKR mapping analytics dashboards and reports, with a 10% reduction in time spent on monitoring progress against objectives.

• Tools/Frameworks: Langchain, FastAPI, JavaScript
• What it does: Integrated OpenAI GPT-3.5 API for document-based question answering, improving accessibility and usability of financial reports and analytics insights. Utilized Langchain with FastAPI and JavaScript to enable natural language interaction, simplifying complex financial data for actionable insights.

• Tools/Frameworks: Python, LSTM, TensorFlow
• What it does: Developed methods to extract event and temporal information from Amharic text. Constructed a dataset of unstructured temporal-triggered news headlines in Amharic. Addressed challenges in disambiguating deverbal nominal entities through rule-based approaches and classical ML models.

• Senior Data Scientist at Kifiya Financial Technologies
  (Led credit scoring initiatives and implemented MLOps practices for digital lending platforms)

• Data Scientist at Tenacious Intelligence Corporation
  (Led development of scoring engines and created business analytics dashboards)

• Text Data Analytics Team Leader at Ethiopian Artificial Intelligence Institute, Ethiopia
  (Led projects in NLP and implemented data pipelines for machine translation)

• Lecturer at Jimma University
  (Developed data science curriculum and conducted research in Natural Language Processing)

• Email: [email protected]
• LinkedIn: Ephrem Tadesse Degu