Data Scientist

SoftPathTechnologies; Dallas (TX); Hybrid; USD 110,000 - 140,000; Full time

Job summary

SoftPathTechnologies in Dallas, TX is seeking a Contract Data Scientist to analyze large-scale datasets, build predictive models, and deliver actionable insights for business problems.

The role operates on a hybrid schedule with three days onsite per week at our Dallas facility, requiring strong Python or R, SQL, and experience with ML libraries.

You will collaborate with data engineering, product management, and business teams to translate analytics into strategic recommendations.

Qualifications

• 3–5+ years of hands-on data science, predictive modeling, and ML in business settings.
• Strong Python or R and advanced SQL for data extraction.
• Experience with Pandas, NumPy, Scikit-learn, XGBoost, and DL frameworks (PyTorch/TensorFlow).
• Familiarity with Tableau/Power BI/Matplotlib/Seaborn.

Responsibilities

• Perform Exploratory Data Analysis and build predictive models.
• Design robust data pipelines and feature engineering for model efficiency.
• Translate model outputs into intuitive visualizations and insights for stakeholders.
• Monitor model performance in production to ensure accuracy and fairness.
• Collaborate with data engineering, product, and business teams.

Skills

Python

SQL

R

Pandas

NumPy

Scikit-learn

XGBoost

PyTorch

TensorFlow

Tableau

Power BI

AWS

Azure

GCP

Education

Bachelor's degree in Data Science, Statistics, CS, or related field

Master's degree in Data Science, Statistics, CS, or related field

Tools

Git

CI/CD

Job description

v (only USC)

Location: Dallas, TX

Work Model: Hybrid

Role Overview

We are seeking an analytical and results-driven Contract Data Scientist to join our team in Dallas, TX. In this role, you will analyze large-scale datasets, build and validate predictive models, and deliver actionable insights to solve complex business problems. This position operates on a hybrid schedule, requiring 3 days onsite per week at our Dallas facility.

Key Responsibilities

• Exploratory Data Analysis & Modeling: Clean, preprocess, and analyze large datasets to develop machine learning algorithms, statistical models, and predictive frameworks.

• Pipeline & Feature Engineering: Design and refine robust data pipelines and feature sets to optimize model efficiency and performance.

• Business Insights & Visualization: Translate complex model outputs and data analyses into intuitive visualizations, reports, and strategic recommendations for stakeholders.

• Model Validation & Maintenance: Continuously test, validate, and monitor model performance in production to ensure accuracy, fairness, and reliability over time.

• Cross-Functional Collaboration: Partner with data engineering, product management, and business domain teams to align data science initiatives with core organizational objectives.

Qualifications & Requirements

• Experience: 3 5+ years of hands‑on experience in data science, predictive modeling, and applied machine learning within a business or enterprise environment.

• Technical Proficiency:

  • Strong programming skills in Python or R, alongside advanced SQL for complex queries and data extraction.

  • Practical experience with core data science libraries (e.g., Pandas, NumPy, Scikit-learn, XGBoost) and deep learning frameworks (PyTorch or TensorFlow).

  • Familiarity with data visualization tools (Tableau, Power BI, or Matplotlib/Seaborn).

  • Cloud platform experience (AWS, Azure, or GCP) for running model workflows and managing data.

Preferred Qualifications

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Applied Mathematics, or a related quantitative field.

• Prior experience working in financial services, healthcare, or corporate technology environments.

• Knowledge of standard software engineering practices (Git, version control, CI/CD).