Kuldeep Singh Sidhu

Data Scientist

Bengaluru, Karnataka, India8 yrs experience

AI ML PractitionerAI Enabled

Key Highlights

8+ years of experience in data science solutions.
Published open-source packages with over 500,000 downloads.
Ranked top 5% on StackOverflow for data science.

Stackforce AI infers this person is a Data Science expert with a focus on AI-driven solutions in E-commerce and Retail.

Contact

Skills

Core Skills

Machine LearningDeep LearningNatural Language Processing

Other Skills

Multi-agent SystemsAI AgentsRecommendation SystemsInformation retrievalSystem designTensorFlowPySparkBERTElasticsearchChatBotData StructuresRASALarge Language Models (LLM)People ManagementSoftware Development

About

- I'm Kuldeep Singh Sidhu, with 8+ years of experience in deploying data science solutions at scale, specializing in machine learning/ deep learning (TensorFlow, PyTorch) and data science (Python). - I have published open-source packages that have garnered 500,000+ downloads collectively. - I frequently answer data science questions on open platforms across the web, currently ranked top 5% on StackOverflow - Passionate about AI (Neural Networks, GANs) and big data analytics (Spark). - Expert in deep learning (CNNs, RNNs) and natural language processing (BERT, GPT, LLama, Mixtral, LangChain). - Skilled in developing AI-driven systems (Keras, Scikit-learn) for business outcomes. - Committed to continuous learning and effective teamwork - Expertise in TensorFlow, PySpark, Elasticsearch, SQL, R, Java, Docker, Kubernetes, and cloud technologies (GCP, AWS, Azure).

Experience

8 yrs

Total Experience

3 yrs 2 mos

Average Tenure

1 yr 7 mos

Current Experience

Walmart

Senior Data Scientist

Oct 2024 – Present · 1 yr 7 mos · Bengaluru, Karnataka, India · Hybrid

Responsible for improving Walmart Search by understanding the search queries made by our 300 million+ monthly active customers to search and recommend 1 billion+ products, thereby impacting our half a trillion+ dollar annual revenue
Built a multi-agent system for fine-grained relevance using LangGraph, resulting in one of the largest GMV uplifts of 300M+

Multi-agent SystemsAI AgentsMachine LearningDeep Learning

Lowe's companies, inc.

Lead Data Scientist

Oct 2020 – Oct 2024 · 4 yrs · Bengaluru, Karnataka, India

Was responsible for improving Lowe’s search experience by understanding 3 billion+ search queries made by our Lowe’s customers on the digital platforms to personalize/recommend 5 million+ products and impact our ∼100 Billion USD revenue annually.
Collaborating across teams to deliver high-performance and low-latency models
Created a Query Classification model for multi-class classification using TensorFlow, PySpark, TensorFlow Serving(TFX) & FastAPI with low latency throughput for search ranking.
Finetuned LLM for Retrieval Augmented Generation (RAG) based on user search query using LangChain with low-latency serving using vLLM and DeepSpeed-MII
Trained a domain-specific BERT to have an accurate & efficient representation of queries and documents related to the home-improvement domain on over 20 million open-source (Semantic Web 2020, Amazon 2018, etc) & in-house data points. The language model outperforms distilled BERT with 20% fewer parameters improving latency.
Conceptualised and built a behavioural tagging model that maps attributes between products and user queries for the top business-driving queries by mining relationships over millions of data points using PySpark.
Expanded search query autocomplete candidate list by 90%+, resulting in more contextual, seasonal and personalised autocomplete suggestions.
Worked on enriching our Elastic Index with user behaviour signals resulting in 16% better recall
Created a 1000 times faster lexical matcher based on SymSpell to compute the importance of each token in a user query for over 3 million + unigrams and bigrams
Created a real-time low latency Spanish Translation model for non-English search queries
Skills: Recommendation Systems, Natural Language Processing, Information retrieval, Deep Learning, System design
Technologies: Tensorflow, PyTorch, Transformers, BERT, Elasticsearch, PySpark, ONNX, FastAPI, GCP, VertexAI

Recommendation SystemsNatural Language ProcessingInformation retrievalDeep LearningSystem designMachine Learning

Justdial

Machine Learning Engineer

Jun 2018 – Oct 2020 · 2 yrs 4 mos · Bengaluru, Karnataka, India

Worked on implementing new features for the JustDial app with 100+ million downloads. Built the very first JD Social (app homepage) content ingestion and recommendation system.
Created a ChatBot with functionalities to serve the user on all 72 verticals (Chatting, Flights, Restaurants, General Search, etc.) that JustDial works on using RASA, SPACY, ChatterBot, Tensorflow, DBPedia
Built a recommendation system for JD Social (JustDial social network) using collaborative filtering and item-based filtering
Created content-based monetizable suggestions. (Eg. suggestion to book tickets to a destination covered in a travel article or buy a product discussed in the article) using BERT (Transfer Learning) with f1 score of 0.88
Summarising news articles using sequence rank to reduce content consumption time.
Researched ways to do Natural Language Processing on Indian Languages
Skills: Natural Language Processing(NLP), ChatBot, Data Structures, System design
Technologies: Tensorflow, scikit-learn, RASA, BERT, Pandas, NumPy, Flask

Natural Language ProcessingChatBotData StructuresSystem designMachine Learning