Job Description

AI ML Data Modeling

Responsibilities

• Gathers interprets and manipulates structured and unstructured data to enable analytical solutions for the business.
• Selects the appropriate modeling technique and/or technology with consideration to data limitations application and business needs.
• Build various ML Models within the Model guidelines and framework.
• Consults with peers for guidance as needed.
• Translates business requirements into specific analytical questions build ML Models and present model outcomes to nontechnical business colleagues.
• Consults with Data Engineering IT the business and other internal stakeholders to deploy analytical solutions
• Stay current with emerging trends and technologies in data quality management data profiling data cleansing tools and AI/ML.
• Collaborate with data governance teams to ensure compliance with regulatory requirements and industry and legal standards related to data quality and privacy.
• Able to identify GenAI use cases given in various business scenarios and come up with possible solutions.
• Familiar with various GenAl technologies Prompt Engineering RAG etc

Skills & Qualifications

• 10 to 12 years of relevant experience and 6 years of experience in data science machine learning quantitative analytics (Mathematics Statistics or Operational Research etc) roles
• Masters degree in computer science Statistics or a related field (Mathematics Operational Research Data Science)
• Experience in Building and validating statistical machine learning and other advanced analytics models.
• Experience in Regression (multiple Logistic etc) Classification (Decision Tree Random Forest XGBoost etc) and Time series Forecasting models (ARIMA) Segmentation NLP Deep Learning and Graph Analytics.
• Experience in Data Mining Python R SQL and familiarity with ML technologies
• Experience in using ML Libraries.
• Working Experience in Domino Data Lab AWS Sagemaker Snowflake are a plus
• Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
• Excellent problemsolving analytical skills and attention to detail with the ability to identify patterns trends and anomalies in data.
• Ability to write code that is easy to follow well documented and commented where necessary to explain logic (high code transparency).
• Experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL HQL NoSQL etc.
• Experience in working with structured semistructured and unstructured data files such as delimited numeric data files JSON/XML files and/or text documents images etc.
• Strong communication and collaboration skills with the ability to effectively interact with technical and nontechnical stakeholders.

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