Tranzeal Incorporated

Data Science Specialist

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Science Specialist in Sunnyvale, CA, with a contract length of "unknown." The pay rate is "unknown." Key skills include strong Python, NLP, machine learning, and data engineering experience. Familiarity with cloud platforms is preferred.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 20, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Sunnyvale, CA
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🧠 - Skills detailed
#Data Engineering #Datasets #Spark (Apache Spark) #Scala #PyTorch #Cloud #SpaCy #Transformers #Deployment #Python #Model Evaluation #ML (Machine Learning) #Programming #Classification #Dataflow #BigQuery #Lambda (AWS Lambda) #Model Deployment #BERT #Data Science #AI (Artificial Intelligence) #Azure #A/B Testing #Data Pipeline #PySpark #NLP (Natural Language Processing) #Automation #"ETL (Extract #Transform #Load)" #GCP (Google Cloud Platform)
Role description
Job Title: Data Science Consultants Location: Sunnyvale, CA (Onsite) Job Description: We are hiring Data Science Consultants with strong experience in Python, NLP, machine learning, data engineering, and model evaluation. The ideal candidate should have hands-on expertise building scalable ML solutions, working with large datasets, and improving search, ranking, recommendation, or NLP-based systems in production environments. Required Skills: • Strong Python programming experience • NLP experience using spaCy, HuggingFace Transformers, BERT, FastText, or semantic matching techniques • Experience with intent classification, entity recognition, and query relevance modeling • Hands-on experience with ML frameworks such as PyTorch, XGBoost, CatBoost, or LightGBM • Knowledge of Learning-to-Rank (LTR), LambdaMART, neural scoring models, or vector search technologies like FAISS/HNSW • Experience with data engineering tools such as PySpark, Dataflow, BigQuery, or pipeline automation • Experience with MLOps, model deployment, artifact versioning, and ML training pipelines • Strong understanding of model evaluation metrics including nDCG, MRR, MAP@K, A/B testing, and statistical significance • Experience building scalable data pipelines and feature engineering solutions Preferred Qualifications: • Experience with GCP, Azure ML, or cloud-based ML platforms • Familiarity with feature stores such as Feast, Tecton, or Cassandra • Experience working on search, recommendation, ranking, or large-scale AI/ML systems