Pradeep Thapa
Melbourne, Victoria
| Phone: 0434233725 | Email: pkthapa@outlook.com |
Summary
A highly skilled Machine Learning Engineer with over 5 years of extensive experience in end-to-end Data Science and Machine Learning projects. My expertise encompasses the entire data science workflow, from meticulous data cleaning and innovative feature engineering to precise model selection and seamless deployment. Furthermore, I possess experience in software engineering and data engineering, which empowers me to design and implement robust and scalable systems capable of handling vast volumes of data efficiently. My dedication to delivering high-quality results and my ability to adapt to emerging technologies have consistently driven successful outcomes for my projects.
My diverse skill set, coupled with my advanced education and hands-on experience, positions me as a valuable asset for data-driven projects and MLOps processes. I am enthusiastic about leveraging my expertise to tackle complex challenges and drive innovation in the field of data science and machine learning.
KEY ACCOMPLISHMENTS
- Managed to maintain an 88% WAM while working and studying full-time.
- Awarded Deakin Scholarship for Excellence 2020
SKILLS & TOOLS
- Python
- SQL
- R
- TensorFlow
- Scikit-Learn
- Machine Learning Algorithms
- Deep Learning
- Software Engineering
- Natural Language Processing
- Computer Vision
- Applied Mathematics
- Data Modelling
- Big Data Analytics
- Data Visualization
- Model deployment
- Cyber Security
- Agile Methodologies
- Data Pipelines (Databricks, Airflow)
- Cloud Platforms (AWS/Azure)
- Containerization (Docker, Kubernetes)
- Big Data Processing Tools (Spark)
Experience
April 2022 – Current
Data Scientist [Customer Decisioning & Data Science, Enterprise Data & Analytics], National Australia Bank (NAB)
- Built scaled analytics processes and capabilities in the target state platform and architecture across the marketing teams.
- Led the development and enhancement of feature store for Marketing analytics and MLOps processes and frameworks such as Model Output, Evaluation, Model Monitoring, etc.
- Led the use of advanced analytical techniques across marketing to provide data driven insights and support strategic decision making across teams.
- Developed end to end data pipelines using AWS to collect required data from various sources and validate the quality of data.
- Development of new or improved analytic techniques to support customers met and un-met financial needs.
July 2021 – April 2022
Machine Learning Engineer [Forensic Technology, Financial Advisory], Deloitte Australia
- Exploratory data analysis and data preparation for model building.
- Develop, validate, test, and deploy deep learning models.
- Apply state-of-the-art algorithms to build the AI capabilities products that the forensic solution team can use.
- Optimise and improve existing machine learning models using model-centric and data-centric approaches.
- Conduct new experiments to tackle some complex forensic problems.
- Prototypes machine learning applications to determine their viability and deploy to staging servers for testing.
- Develop DAGs for ETL pipelines and orchestrate tasks in cloud environment using Airflow.
- Collaborate with developers, data engineers, DevOps engineers and product team to bring ML models to life through training, validating, testing, deployment, and CI/CD pipelines.
- Work on highly impactful projects that are “firsts” within Forensic Technology.
Jul 2017 – Feb 2020
Software Engineer, Corporate Governance Risk
- Create informative, actionable, and repeatable reporting that highlights relevant business trends and opportunities for improvement.
- Identify, design, develop, test, validate and deploy new reports.
- Enhance existing reports and dashboards to improve performance and presentation.
- Work closely with our product build team, and our customer success team to quickly deliver reports & dashboards.
- Create SQL queries to provide ad hoc reports, analysis, and datasets based on business needs.
Education
Master of Applied Artificial Intelligence (Professional), Deakin University, Victoria
2020 - 2021
Major in Applied Artificial Intelligence
Minor in Cyber Security
Bachelor of Computer Science, Edith Cowan University, Western Australia
2014 - 2017
Major in Computer Science
Major in Software Engineering
Western Australian Certificate of Education, Cyril Jackson Campus, Western Australia
2012 - 2014
Certificate I in Information, Communication and Technology (ICT), 2012
Certificate of Excellence for Cert I in ICT, 2012
Certificate of Outstanding Attendance, 2012
Edith Cowan University Citizenship Award, 2012
PROFESSIONAL SKILLS
- Have strong communication skills, analytical and problem-solving skills, the ability to work independently, and a strong focus on quality.
- Proficiency in programming languages such as Python, R and SQL.
- Experience of applying software engineering principles, including design patterns, data structures and algorithms.
- Utilise complex analytic techniques and experimental methods independently to develop technological solutions to achieve business outcomes using computational methods to discover data patterns and to develop classification, prediction, and optimisation models.
- Experience creating and deploying production machine learning models with knowledge of end-to-end data scientist workflows.
- Experience with machine learning libraries and frameworks such as TensorFlow, Scikit-learn, Spark, and PyTorch.
- Experience of using modern Data Engineering tools such as Airflow, Databricks, dbt, Amazon Redshift, and Apache Spark.
- Strong time management skills with the ability to prioritize and contribute to multiple projects simultaneously.
- Ability to read, understand, and communicate technical documentation.
- Experienced user of modern source control (Git), Docker, Kubernetes, and Microsoft Azure services and Amazon Web Services.
CERTIFICATIONS
- AWS Machine Learning Specialty
- Dataricks Lakehouse Data Engineer Associate
- Microsoft Azure Fundamentals
- Microsoft Azure Data Fundamentals
- Microsoft Azure AI Fundamentals
- AWS Cloud Practioner Foundational
- Apache Airflow Fundamentals
- Apache Airflow DAG Authoring
- FINSIA Professional Banking Foundations
AWARDS
Deakin Scholarship for Excellence (2020/21)
This scholarship is designed for students who show exceptional promise within or beyond their academic achievements.
INTERESTS
| Artificial Intelligence | Cricket | Music | Video Games | Trekking |