SASIKALA N · Senior Python / ML Engineer · 6+ yrs
Mid-LevelProof of scale
About SASIKALA
Sasikala N is a Python Developer with 6+ years of experience specializing in AI/ML and full-stack development. She has a proven track record in deploying models and optimizing data pipelines.
6+ years of commercial experience in
Skills(26)
Why hire SASIKALA?
Automated build/deployment processes, reducing human intervention by 40%.
Reduced large dataset processing time by 50% using Pyspark.
Created an Airflow orchestrator pipeline, decreasing manual effort by 30%.
Developed an ML model that increased customer base by 20% by improving complaint resolution.
Successfully automated build/deployment processes, reducing human intervention by 40%.
Created an Airflow orchestrator pipeline that decreased manual effort by 30%.
Project highlights(6)
Emotion-Based Recommendation System – Data Scientist
Overview: This project involved building a labeling model to categorize user emotions and a recommendation system based on these emotions. Responsibilities: Paraphrased the training dataset to increase its size. Fine-tuned the BART model to label events based on given emotions. Built a recommendation system using cosine similarity as the metric. Deployed the BART model using AWS Sagemaker for daily predictions.
Key outcomes:
Successfully developed and deployed an emotion-based recommendation system.
Increased training dataset size through paraphrasing.
Vehicle Repair Prediction Model – Data Scientist
Overview: This project focused on developing a machine learning model to reduce unnecessary vehicle repairs caused by sensor failures. Responsibilities: Used Pinecone to find similarity between user input appliances and PDF embeddings. Employed prompt engineering and OpenAI GPT-4 to extract text from matching PDFs. Created Design of Experiments (DOE) for user input using prompt engineering and OpenAI GPT-4. Predicted DOE outcomes and generated DOE graphs using statsmodels and matplotlib.
Key outcomes:
Developed a model capable of reducing unnecessary vehicle repairs.
Utilized advanced NLP and vector search techniques for information extraction.
Customer Complaint Management Model – Data Scientist
Overview: This project created an ML model to identify problematic customer complaints, enabling companies to take quick action to improve customer satisfaction and retention. Responsibilities: Automated build and deployment using CircleCI to minimize human intervention and speed up production processes by 40%. Created an Orchestrator pipeline from data ingestion to data validation using Airflow, reducing manual effort by 30%. Used Pyspark for transforming large datasets, decreasing processing time by 50% compared to Pandas.
Key outcomes:
Automated deployment, speeding up processes by 40%.
Reduced manual orchestration effort by 30% using Airflow.
Decreased data processing time by 50% using Pyspark.
Contributed to a 20% increase in customer base by enabling proactive complaint resolution.
Product Similarity System – Data Scientist
Overview: This project aimed to calculate product similarity using image and text analysis. Responsibilities: Used pretrained models and custom CNN Models to find similarity in images. Generated IMAGE EMBEDDINGS using pre-trained models. Used ANN to select the 5 most similar images. Calculated image similarity using COSINE SIMILARITY Metrics. Used LSH Algorithm to calculate product name similarity.
Key outcomes:
Developed a comprehensive product similarity system using both visual and textual data.
Successfully applied deep learning models for image embeddings and similarity.
FINETUNING BERT MODEL
- This project focused on fine-tuning a BERT model for specific NLP tasks.
- Worked on EDA to reduce missing values.
- Preprocessed input text, converting it to BERT (LLM) model format.
- Created a metric function using PyTorch to calculate accuracy and F1 score.
Key outcomes:
Successfully fine-tuned a BERT model for specific tasks.
Implemented custom metric functions for performance evaluation.
Industry experience
AI / ML Platform
6 projects- •Emotion-Based Recommendation System— Data ScientistPython · Flask · Numpy · Pandas +6
- •Vehicle Repair Prediction Model— Data ScientistPython · Azure · LangChain · Statsmodels +4
- •Customer Complaint Management Model— Data ScientistPyspark · CircleCI · Docker · Airflow +3
- •Product Similarity System— Data ScientistPython · Flask · Microservice Architecture · Numpy +4
- •FINETUNING BERT MODELNLP · PyTorch · Azure · React.js
- •PRODUCT SIMILARITYPython · Flask · Microservice Architecture · Numpy +4
Automotive
3 projects- •Emotion-Based Recommendation System— Data ScientistPython · Flask · Numpy · Pandas +6
- •Vehicle Repair Prediction Model— Data ScientistPython · Azure · LangChain · Statsmodels +4
- •Customer Complaint Management Model— Data ScientistPyspark · CircleCI · Docker · Airflow +3
FinTech
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SASIKALA N
Python Developer