Data Scientist — ML Pipelines & Transformer Models

Daxwell; Houston (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Daxwell is seeking an experienced Data Scientist to implement machine learning initiatives in an onsite role based in Houston, TX. You will build scalable pipelines, operationalize end-to-end ML workflows, and turn complex data into production-ready models.

You will collaborate with engineering, analytics, and product teams to deploy models and drive data-driven decision making across enterprise applications.

Qualifications

• Master’s or Ph.D. in a quantitative field (CS/Stats/Math).
• Advanced proficiency in Python, PySpark, Pandas, PyTorch.
• Solid ML foundation including GBT and DL architectures (MLP, RNN, Transformers).
• Familiarity with lakehouse architectures Delta Lake and Apache Iceberg.
• Experience with data orchestration/streaming (Airflow, Flink, Kafka); cloud ML deployments (EKS, EMR).
• Strong communication to translate complex insights for stakeholders.

Responsibilities

• Architect scalable data ingestion, transformation, and training pipelines.
• Prepare, clean, and feature-engineer large-scale data sets; ensure quality and reproducibility.
• Conduct inference, EDA, and causal validation to generate actionable insights.
• Select, train, validate, and deploy supervised and unsupervised models.
• Build transfer learning and fine-tuning pipelines with pretrained transformers.
• Design and automate end-to-end ML workflows: training, evaluation, feature versioning, serving.

Education

Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or related quantitative discipline

Tools

Python

PySpark

Pandas

PyTorch

Delta Lake

Apache Iceberg

Airflow

Flink

Kafka

EKS

EMR

GBT

MLP

RNN

Transformers

Job description

Daxwell is seeking an experienced Data Scientist to implement machine learning initiatives in an onsite role based in Houston, TX. You will build scalable pipelines, operationalize end-to-end ML workflows, and turn complex data into production-ready models.

You will collaborate with engineering, analytics, and product teams to deploy models and drive data-driven decision making across enterprise applications.