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Data Scientist
Job Description
- Primary skills: Technology->Data Science->Machine Learning, Technology->Machine learning->data science
- Partner with stakeholders to translate business goals into data science problem statements, success metrics, and experiment plans.
- Build, evaluate, and deploy machine learning and AI models using Python, ensuring performance, robustness, and scalability.
- Develop NLP solutions such as text classification, entity extraction, topic modeling, semantic search, and summarization based on use case needs.
- Perform end-to-end data science workflows: data collection, cleaning, feature engineering, model training, validation, and monitoring.
- Experience building and optimizing NLP systems using modern approaches (e.g., embeddings, transformer-based models) and tailoring them to domain needs.
- Proven ability to design experiments, run A/B tests, and connect model improvements to measurable business outcomes.
More Info
Key Skills
Feature Engineering
Transformer-based Models
Model Training
Topic Modeling
Embeddings
About Company
Skills:
Matplotlib, Sql, Tensorflow, Tableau, Numpy, Rest Apis, Azure Machine Learning, Pandas, Seaborn, Power Bi, Cloud Services, Pytorch, Python, Git, MLflow, Hugging Face, Scikit-learn, Azure OpenAI, CI CD, Jupyter, LangChain, SpaCy, LangGraph
Skills:
Hadoop, SAS, MATLAB, Sql, Nosql, MySQL, Spss, Spark, Oracle, Python, Teradata, R
Skills:
Machine Learning, Tensorflow, Numpy, Pytorch, Docker, Python, Sql, Pandas, FastAPI, Hugging Face, MLflow, LangGraph, LangChain, Generative AI, Scikit-learn
Skills:
Matplotlib, Sql, Tensorflow, Pytorch, Gcp, Seaborn, Azure, Python, AWS, Airflow, scikit-learn, MLflow
Skills:
Pyspark, Apache Hadoop, Machine Learning, Apache Spark, Sql, Devops, Data Science, Numpy, Pandas, Powerbi, Agile, Cloudera, Databricks, Azure, Rapidminer, Python, Big data frameworks, Scikitlearn