Specialist - Data Sciences

Role Description

Position Role AIML Developer

Indicative Responsibilities

Design develop and deploy machine learning and deep learning models to assess and predict risks detect anomalies identify patterns in data structured and unstructured data and derive actionable insights from data

Clean preprocess and engineer features from large datasets to ensure highquality input for machine learning models

Train validate and optimize models for performance and accuracy ensuring they meet business requirements

Tailor risk assessment strategies to address specific risk categories including recovery risks litigation risks and noncompliance related to different classes of entities like taxpayers deductors and reporting entities

Implement scalable AI and ML solutions ensuring models can handle large volumes of data and integrate with existing and new systems

Manage the complexities of data integration ensuring accuracy and relevance for risk analysis and seamless integration with diverse data sources such as financial statements transaction records regulatory filings and thirdparty databases

ML Model deployments and serving

Model Monitoring Management and Governance

Work closely with data scientists data analysts and IT teams to integrate machine learning solutions into broader risk management frameworks

Monitor model performance postdeployment troubleshoot issues and continuously improve models based on new data or evolving risk factors

Document algorithms workflows model parameters and provide clear reports on model performance and risk predictions to stakeholders

Minimum Qualification

BE B Tech M Tech MCA or Equivalent

Min 5 years of experience as Developer and 2 years of experience in AIML development with a focus on applying machine learning and artificial intelligence techniques

Experience with endtoend model development including data preprocessing model training validation and deployment

Strong programming skills in Python R etc as well as proficiency in ML libraries such as Pandas NumPy TensorFlow Keras Scikitlearn etc

Expertise in developing and deploying machine learning models and implementing MLOps best practices

Strong analytical and problemsolving abilities to tackle complex issues and optimize machine learning models