The Role
Build and deploy production NLP classification models for customer messages and call transcripts. Develop intent, topic, sentiment, and multi-label taxonomies; clean and prepare sensitive text data; create scalable Python and PySpark pipelines; design labeled datasets and annotation workflows; detect trends and anomalies; and monitor precision, recall, confidence, confusion patterns, false alerts, and model drift.
Summary Generated by Built In
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
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
Skills Required
- 4-6+ years of data science, machine learning, NLP, or relevant experience
- Experience with NLP classification for customer messages or call transcripts
- Experience with intent, topic, sentiment, and multi-label classification
- Experience with confidence scoring and model evaluation
- Experience with text cleaning, deduplication, speaker handling, and PII-safe processing
- Experience with trend and anomaly detection
- Python, PySpark, SQL, and pandas
- Experience designing labeled datasets and annotation workflows
- Knowledge of precision, recall, confusion matrices, and drift monitoring
- 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 scalable data pipelines
- Experience creating and validating labeled datasets
- Understanding of model evaluation, monitoring, and false-alert reduction
- Experience working with governed or PII-bearing data
- Databricks experience
- Unity Catalog experience
- Databricks Workflows experience
- MLflow experience
- Model and data versioning experience
- Retrieval and embedding model experience
- LLM-assisted classification with evaluation and guardrails
- Contact-center or customer-support analytics experience
- Property-management or real-estate data experience
- Work authorization: GC, USC, or valid EAD other than H1B, OPT, or CPT
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Often, the biggest barrier between setting business objectives and achieving them is talent. Finding technically qualified people when you need them is hard enough. Finding technically qualified people who are the best fit for your organization is tougher. You need a staffing partner with the right expertise who can find the right talent in the right time frame, because your project can’t wait. That’s where we come in. aKube Inc is committed to leveraging its corporate values and operating model to achieve the highest level of performance and respect within the industry. We have developed a highly efficient delivery model for supporting a wide array of clients with expertise in supporting high-volume contingent worker programs.
.png){kind=logo}
