Senior Data Scientist / Machine Learning Engineer, NLP - 1635

aKube

  • Calabasas, California
  • 14 days ago

    Highlights

    Build trend and anomaly detection methods using baselines, seasonality, and channel mix. Define sampling strategies and annotation guidelines for labeled datasets.

    Numbers & Facts

    LocationCalabasas, California
    Websiteakubeinc.com

    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


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