Summary
✨ AI‑Generated
Join a dynamic team working on advanced NLP classification models for customer communications. You'll develop intent, topic, and sentiment taxonomies, clean and prepare transcript data, and handle complex text processing including deduplication and PII-safe handling. Perfect for someone with 4-6+ years of data science experience who excels in Python and ML frameworks. Must be authorized to work in the US (GC, USC, or valid EAD).
Highlights
6-month contract role with competitive rate. Work on cutting-edge NLP projects involving intent classification, sentiment analysis, and multi-label taxonomy development. Hybrid work arrangement with flexible onsite requirements.
Description
City: Las Vegas, NV / Calabasas, CA
Onsite/ Hybrid/ Remote: Hybrid Calabasas (Monday-Wednesday in office) , Las Vegas (5 days onsite)
Duration: 6 months
Rate Range: Upto $85/hr on W2
Work Authorization: GC, USC, All valid EADs except H1B, OPT, CPT
Must Have:
4–6+ years of data science or machine learning experience
NLP classification for customer messages or call transcripts
Intent, topic, sentiment, and multi-label classification
Confidence scoring and model evaluation
Text cleaning, deduplication, speaker handling, and PII-safe processing
Trend and anomaly detection
Python, PySpark, SQL, and pandas
Labeled dataset design and annotation workflows
Precision, recall, confusion matrix, and drift monitoring
Responsibilities:
Build and deploy NLP classification models for customer communications.
Develop intent, topic, sentiment, and multi-label taxonomies.
Clean and prepare transcript and message data for modeling.
Handle short-text cases, duplicate records, system messages, and speaker identification.
Build trend and anomaly detection methods using baselines, seasonality, and channel mix.
Design maintainable Python and PySpark data pipelines.
Define sampling strategies and annotation guidelines for labeled datasets.
Support reviewer adjudication and dataset quality validation.
Track model precision, recall, confusion patterns, confidence scores, and drift.
Implement secure processing for customer communications containing sensitive data.
Qualifications:
4–6+ years of relevant machine learning, NLP, or data science experience.
Proven experience deploying NLP models into production.
Strong experience with classification systems and text analytics.
Advanced Python development and testing skills.
Hands-on experience with PySpark, SQL, pandas, and scalable data pipelines.
Experience creating and validating labeled datasets.
Strong understanding of model evaluation, monitoring, and false-alert reduction.
Experience working with governed or PII-bearing data.
Nice to Have:
Databricks
Unity Catalog
Databricks Workflows
MLflow
Model and data versioning
Retrieval and embedding models
LLM-assisted classification with evaluation and guardrails
Contact-center or customer-support analytics
Property-management or real-estate data experience
