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Valikala Chandra

@valikalachandra

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Data Scientist building production ML, NLP, and GenAI evaluation systems.

India

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What I'm looking for

I’m excited to build production ML/NLP/GenAI evaluation systems, ship reliable models, and design data pipelines using experiments and MLOps—partnering with teams that value rigorous measurement and fast iteration.

I’m a Data Scientist with 2+ years building production ML, NLP, and GenAI evaluation systems across advertising, manufacturing, aerospace, and healthcare. I focus on turning models into reliable products using strong experimentation, analytics, and MLOps.

In production roles, I built a TTD agent with a LangSmith evaluation harness (routing, tool calling, context, memory) to improve agent reliability, and engineered Databricks + PySpark workflows for large-scale preprocessing and deduplication. I’ve also deployed models on AWS SageMaker with MLflow and automated ML pipeline feature engineering to cut training and release cycles.

I’m energized by end-to-end problem solving—from reinforcement learning decision models for mission planning and transformer-based extraction over 50,000+ papers, to computer vision and recommendation systems. With AWS and Azure AI credentials, I bring a measurement-first mindset to model evaluation, monitoring, and continual improvement.

Experience

Work history, roles, and key accomplishments

Current

Product Data Science Intern

Current

MiQ Digital

Jan 2026 - Present (4 months)

Developed a TSA TTD activation agent tool and LangSmith evaluation harness for routing, tool calling, context, and memory, improving reliability of production data-science agents. Built Databricks + PySpark preprocessing workflows for large-scale deduplication supporting DSP/RTB campaign analytics.

Langsmith Agentic AI LLM Evaluation Databricks Pyspark data preprocessing And Deduplication

Data Scientist Intern

Tvarit GmbH

May 2025 - Jul 2025 (2 months)

Deployed XGBoost/Random Forest predictive-maintenance models on AWS SageMaker using MLflow, achieving 89% accuracy and reducing release cycle by 35% and operational costs by 15%. Productionized a CNN defect detection pipeline reaching 96% accuracy to remove manual QC bottlenecks in manufacturing.

AWS Sagemaker MLFlow XGBoost Random Forest Predictive Maintenance Computer Vision

Data Science Research Intern

ISRO SHAR SDSC

Dec 2024 - Jan 2025 (1 month)

Built reinforcement learning decision models for mission-planning use cases, improving accuracy by 25% and cutting compute time by 40% via trajectory optimization. Developed transformer-based NLP extraction over 50,000+ research papers, reducing literature review time by 70% for senior scientists.

Reinforcement Learning Decision Models

Data Scientist Intern

Intraintech-SkillCepha

Jan 2024 - Mar 2024 (2 months)

Architected a collaborative-filtering recommendation engine delivering a 28% CTR lift while serving 1M+ interactions/hour with low-latency real-time inference. Automated feature-engineering ETL to cut training time by 50% and validated ranking quality using NDCG and precision@K prior to production rollout.

Recommendation Systems Collaborative Filtering Feature Engineering ETL Ranking Metrics (NDCG Machine Learning Precision@K

Education

Degrees, certifications, and relevant coursework

Vellore Institute of Technology

B.Tech in Computer Science and Engineering, Computer Science and Engineering (Artificial Intelligence and Machine Learning)

Grade: CGPA: 9.50/10.0

Activities and societies: Relevant coursework includes Machine Learning, Deep Learning, Computer Vision, Digital Image Processing, NLP, Statistics & Probability, Linear Algebra, and Optimization Methods.

Pursuing a B.Tech in Computer Science and Engineering with a specialization in Artificial Intelligence and Machine Learning, with coursework covering machine learning, deep learning, NLP, and optimization. Expected to complete in June 2026.