Bikal Basnet

WORK HISTORY

EDUCATION

SKILLS

ABOUT BIKAL BASNET

Passionate Data scientist with numerous projects spearheaded, piloted, and ignited. I am also a• Udacity Certified Machine Learning Nanodegree Engineer• Cloudera Certified Hadoop Developer• 10+ years of experience with 6+ years as Data Scientist, 2+ as Data Engineer, 2+ as web developer working at Fast-Paced Startups(2)• 10+ Tensorflow, 12+ Python, 5+ MS SQL, 3 R, 1 Scala/Spark Project and countingData Scientist • Researched / Developed 8+ production-level models for Classification (Intent Classification, ProductDeduplication / Matcher), Entity Extraction, DYM Identifier, Product Recommendation (Spark/Scala), Forecasting & Enterprise Search using classical & advanced statistical models - Classical i.e Regression, Tree, Random Forest, SVM, DNN to advanced i.e DNN, CRF, Convolution Neural Networks(convNets), LSTM, Self-attention models, Seq2Seq, ULMFit, Transformers, BERT, BERT Siamese Network • Transfer Learning: Fine-tuned SOA Transformer Models i.e BERT to Insurance domain• Hands-on experience with Time-Series Forecasting (Demand Forecaster ), Image Data / Computer Vision - Digit Identification with Regression/NN/ConvNets), Clustering / Segmentation (K-means), and Reinforcement Learning(Q-Learning Based Traffic Rule Learning Agent) • Experience using NLP tools/ libraries i.e word2vec, doc2vec, spacy, Hugging Face, BERT, Gensim, • Good Knowledge of AWS Sagemaker, Advanced Language Models (GPT, Reformers, MUM, PAML) & Basic Knowledge of Auto-encoders, Generative Adversarial Neural Networks (GANs) • Experience working in Agile Development ( Scrum ) environment, Git Workflow, BI, Visualization Tools ( Tableau, Metabase ) & MLOps (Docker, Packer, BitBucket Pipeline, Terraform)Big Data Engineer• Proposed/Spearheaded Scala/Spark-based Data Adapters for 10GB+/store of raw log data• Installed 4-node Hadoop Cluster [Fun Project] • Performed Analysis on 5GB+ Structured flat file data - Java [Fun Project] Toolset : • Language: TensorFlow (10+), Python (12+ Projects: Scikit-learn, Pandas), Scala (1), • ML Algorithms Classical: Tree (3), Forest (2), Regression (5), Naive Bayes (1), Clusters (2) Advanced: SVM (3), NN (1), LSTM (1), Enc-Dec. LSTM+Glove (1), ConvNets (1), Word2Vec-SkipGram (1), CBOW (1), UlmFit(1), BERT(4), Reinforcement Learning(1), Language Generation(1)• Database/Big Data SQL: TSql(:4+), Spark (1), AWS Redshift (1), AWS GLUE(1)• Visualization : Matplotlib (12+), Seaborn (4+), Tableau (1), Jasper Soft (1)• DevOps / AWS Tools: Docker, Packer, Terraform, AWS SageMaker