Back
Metro location, broad ML/data skillset requirements and hybrid work raise candidate competition.
ML and data engineering skills transfer across industries, though financial domain and Power Apps increase domain specificity.
Mandatory 7+ years plus extensive ML, Snowflake, Power BI, and Power Apps skills enforce strict shortlisting.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop, deploy, and maintain machine learning models to solve complex business problems and support decision-making.
Design and implement data pipelines using Python, Snowflake, and Oracle ensuring data quality and integrity throughout the ETL process.
Create and optimize interactive dashboards and automation solutions using Power BI, Power Apps, and Power Automate to enhance operational efficiency and visualize key business metrics.
Minimum 7 years of experience in data science, analytics, or related roles focused on machine learning.
Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or related field.
Strong proficiency in Python programming and machine learning libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch).
Hands-on experience with Power BI, Power Apps, Power Automate, Snowflake, Oracle databases, and advanced SQL skills.
Experienced in end-to-end machine learning lifecycle including data preprocessing, feature engineering, model training, and evaluation.
Capable of leading technical initiatives and mentoring junior team members with deep knowledge of data visualization and automation platforms.
Able to bridge technical and business teams by translating complex technical concepts into actionable business insights.