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I am a data scientist focused on turning data into tangible business value. With 11+ years of hands-on experience across healthcare, finance, and cloud-native environments, I design and deploy end-to-end AI/ML solutions, including Generative AI and data engineering platforms. I enjoy collaborating with cross-functional teams to translate complex problems into scalable, observable, and governance-ready products. My approach combines robust modeling, responsible AI practices, and practical engineering to deliver measurable impact for regulatory contexts and real-world workflows. I thrive on building production-grade ML systems that stay aligned with business needs, offer explainability, and adapt to evolving data. I actively pursue continuous learning, mentor colleagues, and advocate for transparent, auditable AI solutions that balance innovation with risk management.…I am a data scientist focused on turning data into tangible business value. With 11+ years of hands-on experience across healthcare, finance, and cloud-native environments, I design and deploy end-to-end AI/ML solutions, including Generative AI and data engineering platforms. I enjoy collaborating with cross-functional teams to translate complex problems into scalable, observable, and governance-ready products. My approach combines robust modeling, responsible AI practices, and practical engineering to deliver measurable impact for regulatory contexts and real-world workflows. I thrive on building production-grade ML systems that stay aligned with business needs, offer explainability, and adapt to evolving data. I actively pursue continuous learning, mentor colleagues, and advocate for transparent, auditable AI solutions that balance innovation with risk management.

Sindhu Pandi

Data Scientist, AI Engineer, Full Stack Developer, +2

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I am a data scientist focused on turning data into tangible business value. With 11+ years of hands-on experience across healthcare, finance, and cloud-native environments, I design and deploy end-to-end AI/ML solutions, including Generative AI and data engineering platforms. I enjoy collaborating with cross-functional teams to translate complex problems into scalable, observable, and governance-ready products. My approach combines robust modeling, responsible AI practices, and practical engineering to deliver measurable impact for regulatory contexts and real-world workflows. I thrive on building production-grade ML systems that stay aligned with business needs, offer explainability, and adapt to evolving data. I actively pursue continuous learning, mentor colleagues, and advocate for transparent, auditable AI solutions that balance innovation with risk management.…I am a data scientist focused on turning data into tangible business value. With 11+ years of hands-on experience across healthcare, finance, and cloud-native environments, I design and deploy end-to-end AI/ML solutions, including Generative AI and data engineering platforms. I enjoy collaborating with cross-functional teams to translate complex problems into scalable, observable, and governance-ready products. My approach combines robust modeling, responsible AI practices, and practical engineering to deliver measurable impact for regulatory contexts and real-world workflows. I thrive on building production-grade ML systems that stay aligned with business needs, offer explainability, and adapt to evolving data. I actively pursue continuous learning, mentor colleagues, and advocate for transparent, auditable AI solutions that balance innovation with risk management.

Available to hire

I am a data scientist focused on turning data into tangible business value. With 11+ years of hands-on experience across healthcare, finance, and cloud-native environments, I design and deploy end-to-end AI/ML solutions, including Generative AI and data engineering platforms. I enjoy collaborating with cross-functional teams to translate complex problems into scalable, observable, and governance-ready products. My approach combines robust modeling, responsible AI practices, and practical engineering to deliver measurable impact for regulatory contexts and real-world workflows.

I thrive on building production-grade ML systems that stay aligned with business needs, offer explainability, and adapt to evolving data. I actively pursue continuous learning, mentor colleagues, and advocate for transparent, auditable AI solutions that balance innovation with risk management.

Skills

Experience Level

Expert

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Expert

Work Experience

Senior Data Scientist (Gen AI) at Allspring Global Investments

August 1, 2023 - Present

Led the design and deployment of a GenAI platform for financial document intelligence, employing GPT-4, BERT, and T5 to automate processing of earnings reports, SEC filings, and investment research, reducing analyst research time and accelerating information retrieval. Implemented supervised fine-tuning and RLHF to align domain-specific models with investment terminology. Built Retrieval-Augmented Generation pipelines using FAISS and Pinecone with LangChain, enhancing search precision and reducing hallucinations. Architected ETL pipelines with PySpark and SQL, built a data lakehouse on AWS and Snowflake for scalable storage and unified analytics. Established MLOps pipelines with Docker, Kubernetes, MLflow, Jenkins, GitHub Actions, and Terraform, including model versioning and drift monitoring. Implemented real-time data ingestion via Kafka and Spark Streaming, and integrated multi-cloud search frameworks. Designed multi-agent LangGraph-based workflows for document retrieval, financial

AI/ML Engineer at TD Bank

June 1, 2020 - July 31, 2023

Developed and deployed ML models for credit risk, fraud detection, and churn; achieved 28% improvement in prediction accuracy. Built SHAP and LIME-based explainability frameworks for regulatory compliance and auditability. Created time-series forecasting and anomaly detection using TensorFlow/PyTorch. Implemented NLP/document processing and chatbots with spaCy/NLTK/Hugging Face to enhance customer interactions. Directed RAG and semantic search for banking knowledge systems; built vector embeddings for internal repositories. Led end-to-end MLOps with Docker, Kubernetes, MLflow, CI/CD; deployed models to AWS/Azure/GCP; implemented streaming data pipelines via Kafka and Spark Streaming for near real-time scoring. Designed A/B testing framework and model validation to ensure safe promotions. Implemented reinforcement learning for portfolio optimization and risk management. Built dashboards in Tableau/Power BI; collaborated with risk teams to translate requirements.

Data Scientist at Geico

September 1, 2017 - May 31, 2020

Created predictive models for claims forecasting, risk segmentation, and severity; built CNN-based computer vision for damage assessment; migrated insurance data to Snowflake; developed NLP pipelines for claims document processing; built scalable ETL pipelines with Spark/Dask; deployed SageMaker models; implemented RAG and semantic search for knowledge systems; automated reporting and dashboards; built anomaly detection for fraud and monitoring; established governance and drift detection; led cross-functional collaboration with business units to translate requirements into scalable AI solutions.

Data Analyst / Junior Data Scientist at State of Florida

February 1, 2014 - August 31, 2017

Evaluated and streamlined government processes; built Tableau dashboards for state reporting; developed predictive analytics; built deep learning models for image, video, and text analysis; fraud detection; data pipelines to consolidate multi-source datasets; geospatial analysis; regulatory reporting; data preprocessing and Python/SQL automation for recurring reporting tasks; cross-functional collaboration and UAT support.