Back
Tier-1 brand, popular ML role, metro location, and broad skillset drive high applicant competition.
Requires financial enterprise analytics and regulated environment experience, limiting cross-industry transferability.
Explicit 8-12 years requirement plus mandatory ML/MLOps tools and financial data experience increases strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead design and execution of complex data analysis and AI/ML projects on large structured and unstructured datasets.
Manage delivery including volume, quality, and timeliness of data science projects with resource planning responsibilities.
Collaborate with stakeholders and Data Engineering teams to operationalize machine learning models and ensure compliance with model governance and regulatory requirements.
8-12 years of experience in Data Analytics, Data Science, or Advanced Analytics roles.
Strong programming skills in Python (required), PySpark preferred; advanced proficiency in SQL and relational databases.
Hands-on experience with ML model development and deployment, including libraries like scikit-learn, XGBoost, TensorFlow, or PyTorch.
Bachelor’s degree required; Master’s or specialization in AI/ML/Data Science preferred.
Experienced in enterprise or financial services domain with large-scale data and regulated environments.
Demonstrated ability to communicate complex AI/ML insights effectively to non-technical senior leadership and cross-functional teams.
Capable of managing multiple priorities in fast-paced settings and mentoring junior analysts on advanced analytics and ML best practices.