Proven experience as a Data Engineer in a software development environment.
Strong understanding of Data Integration
Excellent communication, facilitation, and coaching skills.
Ability to work collaboratively in a fast-paced environment.
Proficient in Python and Machine Learning
Python Development:
Develop, test, and maintain high-quality Python code
Utilize advanced Python features, including classes and object-oriented programming, to create efficient and reusable code.
Leverage data manipulation libraries such as Pandas and NumPy to process and analyze large datasets effectively.
Machine Learning Integration:
Collaborate with cross-functional teams to integrate ML models into existing systems and applications.
Apply knowledge of basic ML algorithms, including Linear Regression, Logistic Regression, and Random Forest, to solve real-world problems.
Identify key outcomes of ML models and communicate findings to stakeholders in a clear and concise manner.
Statistical Analysis:
Conduct statistical hypothesis testing to validate model results and ensure the reliability of conclusions drawn from data.
Interpret the results of statistical analyses and present insights in a client-facing manner, ensuring that complex concepts are easily understood by non-technical audiences.
Cloud Technologies:
Utilize Azure Cloud services and Azure Databricks for data processing, model training, and deployment.
Optimize cloud resources to enhance performance and reduce costs associated with ML projects.