Senior Data Scientist / Machine Learning Engineer, NLP - 1635

aKube; Calabasas (CA); On-site; USD 70,257 - 117,096; Full time

Job summary

aKube in Calabasas is seeking a Senior Data Scientist / ML Engineer (NLP) to design and deploy classification models for customer messages and transcripts. The role is hybrid with Calabasas in-office days and Las Vegas onsite.

You will build intents, topics, sentiment, and multi-label taxonomies, clean data, and implement secure processing. Requires 4–6+ years, strong Python, PySpark, SQL, and pandas skills, plus experience with labeled data and model monitoring.

Qualifications

• 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.
• Hands-on experience with governed or PII-bearing data.

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.

Skills

Python

PySpark

SQL

Pandas

NLP

ML deployment

Text processing

PII handling

Model evaluation

Sentiment analysis

Tools

Databricks

MLflow

Unity Catalog

Databricks Workflows

Job description

Senior Data Scientist / Machine Learning Engineer, NLP - 1635

Calabasas, United States | Posted on 07/15/2026

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