Data Mining Engineer
Must Have Technical/Functional Skills
" Analyze large structured and semi-structured datasets to identify patterns, trends, and relationships.
" Apply data mining techniques such as clustering, classification, association rules, and anomaly detection.
" Build and validate analytical and predictive models to support business decision-making.
" Perform data preparation activities including data cleaning, transformation, and feature engineering.
" Collaborate with business stakeholders to translate business problems into analytical use cases.
" Work closely with data engineering and data science teams to operationalize insights.
" Develop dashboards, reports, and presentations to communicate insights effectively.
" Ensure data quality, governance, and compliance with enterprise and regulatory standards.
" Explore and apply AI/ML techniques to enhance analytical insights where applicable.
Roles & Responsibilities
" Strong experience in data mining and statistical analysis on large datasets.
" Proficiency in SQL for data extraction and analysis.
" Hands-on experience with Python and/or R for data analysis and modeling.
" Knowledge of data mining and ML algorithms (e.g., decision trees, random forest, regression, clustering).
" Experience with data visualization tools (Power BI, Tableau, or similar).
" Strong analytical thinking and problem-solving skills.
" Ability to work with large datasets in enterprise environments.
Preferred / Good-to-Have Skills
" Experience in BFSI domain (banking, cards, risk, fraud, customer analytics).
" Exposure to Big Data technologies (Spark, Hadoop).
" Experience with AI-driven analytics or GenAI-based insight generation.
" Familiarity with cloud platforms (GCP).
" Understanding of data governance, privacy, and regulatory requirements.
" Analyze large structured and semi-structured datasets to identify patterns, trends, and relationships.
" Apply data mining techniques such as clustering, classification, association rules, and anomaly detection.
" Build and validate analytical and predictive models to support business decision-making.
" Perform data preparation activities including data cleaning, transformation, and feature engineering.
" Collaborate with business stakeholders to translate business problems into analytical use cases.
" Work closely with data engineering and data science teams to operationalize insights.
" Develop dashboards, reports, and presentations to communicate insights effectively.
" Ensure data quality, governance, and compliance with enterprise and regulatory standards.
" Explore and apply AI/ML techniques to enhance analytical insights where applicable.
Roles & Responsibilities
" Strong experience in data mining and statistical analysis on large datasets.
" Proficiency in SQL for data extraction and analysis.
" Hands-on experience with Python and/or R for data analysis and modeling.
" Knowledge of data mining and ML algorithms (e.g., decision trees, random forest, regression, clustering).
" Experience with data visualization tools (Power BI, Tableau, or similar).
" Strong analytical thinking and problem-solving skills.
" Ability to work with large datasets in enterprise environments.
Preferred / Good-to-Have Skills
" Experience in BFSI domain (banking, cards, risk, fraud, customer analytics).
" Exposure to Big Data technologies (Spark, Hadoop).
" Experience with AI-driven analytics or GenAI-based insight generation.
" Familiarity with cloud platforms (GCP).
" Understanding of data governance, privacy, and regulatory requirements.
Easy Apply