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Senior Data Scientist / Machine Learning Engineer, NLP - 1635

aKUBE

HybridLos Angeles, CA · +1 moreseniorUp to $85/hrPosted 7h ago
2 locationsLos Angeles, CACalabasas, CA

Job 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