Senior Data Scientist

Ovii's Interpretation of the Role

Gradera seeks a senior data scientist to turn complex, real‑world data into actionable insights and production‑grade machine‑learning solutions. The role spans the full data lifecycle, partnering with engineers and business stakeholders across the Dallas‑Fort Worth area.

Role Snapshot

• Senior Data Scientist
• Hybrid (DFW) location
• Client‑facing
• Machine Learning & Analytics
• Python / R
• SQL & Databricks
• MLOps on cloud

Must-Have Requirements

• Python (pandas, NumPy, scikit‑learn, PyTorch/TensorFlow)
• R
• SQL (DB2, SQL Server)
• Databricks
• Data warehouse platforms (Databricks, Snowflake, Redshift)
• MLOps tools (MLflow, Kubeflow, Airflow)
• Streaming technologies (Kafka, Spark)
• Statistical foundations (probability, statistics, linear algebra, experimental design)
• Customer‑facing communication
• Data Science
• Machine Learning
• Statistical analysis
• Client‑facing
• Must reside in or relocate to Dallas/Fort Worth
• Must attend client meetings in person

Nice-to-Have Signals

• Deep learning, NLP, computer vision, Bayesian methods
• Real‑time streaming pipeline experience
• Open‑source contributions or published research
• Azure or AWS
• Deep learning
• NLP
• Computer vision
• Bayesian methods

Work Setup

• Location: Dallas/Fort Worth, USA
• Work mode: HYBRID
• Relocation: Must be located in or willing to relocate to Dallas/Fort Worth
• Travel: Travel to client sites throughout DFW as needed
• Employment type: Full-Time

Eligibility Gates

• Visa sponsorship: unknown

Not Specified in JD

• Visa sponsorship
• Salary range
• Remote eligibility
• Education requirement
• Certifications
• Background check

What You'll Likely Work On

• Collect, clean, and profile large structured and unstructured datasets from multiple sources
• Perform exploratory data analysis, data quality audits, and lineage documentation
• Create analytical datasets and feature stores ready for modeling
• Develop and deploy ML models (regression, classification, clustering, NLP, time‑series)
• Design and evaluate A/B experiments using causal inference techniques
• Collaborate with data engineers to build reliable pipelines and MLOps workflows
• Monitor models in production and build self‑serve dashboards for stakeholders

Good Fit If You Have

• Experience with deep learning, NLP, computer vision, or Bayesian methods
• Familiarity with real‑time or streaming data pipelines
• Open‑source contributions or published research