Promantus, Inc

Promantus, Inc

Urgent Opening - Data Scientist with GEN AI - Plano, TX - 12+Month - Onsite

Plano, Texas, USA · third party, contract

Sponsorship not specifiedDetected 154 days ago
PythonAlgorithmsSQLNoSQLPostgreSQLMongoDBDatabricksAzureSparkData ScienceNLPLLMs

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odds of building a lasting career here

37Risky
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Third-party placement is common here

20% of this employer's visa filings place the worker at a client company rather than at the employer itself. Your visa, salary band and layoff exposure would follow the employer of record, not the client.Most common: United Services Automobile Association (USAA)Files as an H-1B dependent employer.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • Aarif Raja Email: Linkldin: Promantus Inc

Requirements

  • DS models design, development and training/validation, LLM Fine-tuning knowledge required.

Nice to have

  • Strong coding and DE skills will be plus.

Skills

  • Hi Employers / Bench Sales / Candidates, This is Aarif, Technical Recruiter from Promantus.
  • Kindly review the job details below and share suitable profiles / your updated resume if interested.
  • Scientist Location:
  • TX Duration:
  • 12+Month Need Min 05+Years
  • Hands-on experience in Python, Pyspark/Spark, NO-SQL (MongoDB), SQL- PostgreSQL, Databricks, Azure Cloud Thanks & Regards..?

This listing is sourced directly from Promantus, Inc's careers page and normalized into a canonical job model.