Data Scientist

  • The Woodlands, TX
  • Posted 2 days ago | Updated 2 days ago

Overview

Hybrid
Depends on Experience
Contract - Independent
Contract - W2
Contract - 12 Month(s)
No Travel Required
Unable to Provide Sponsorship

Skills

Algorithms
Artificial Intelligence
Machine Learning (ML)
Data Science
Python
Amazon Web Services
Machine Learning Operations (ML Ops)

Job Details

Job Title: Data Scientist

Job Summary

We are looking for a skilled Data Scientist who can extract meaningful insights from complex data, build predictive models, and drive data-informed decisions across the organization. The role involves collecting, processing, and analyzing large datasets, developing machine learning solutions, and communicating results to technical and non-technical stakeholders.

Key Responsibilities

Data Collection & Preparation

  • Gather, clean, preprocess, and validate large structured and unstructured datasets from multiple sources.
  • Ensure data quality, consistency, and accessibility for analysis.

Modeling & Analysis

  • Develop, test, and deploy predictive models, machine learning algorithms, and statistical analyses to solve business problems. 
  • Perform exploratory data analysis to identify trends, patterns, and actionable insights.

Visualization & Reporting

  • Create dashboards, reports, and visualizations to present results clearly and effectively to stakeholders.
  • Translate complex findings into business recommendations and storytelling.

Collaboration

  • Work closely with cross-functional teams (product, engineering, finance, marketing) to understand data needs and integrate analytical solutions.
  • Communicate insights and model results to both technical and non-technical audiences.

Model Deployment & Monitoring

  • Collaborate with data engineers or ML engineers to operationalize models and monitor their performance in production.
  • Ensure data science solutions are scalable, robust, and maintainable.

Continuous Learning

  • Stay updated with emerging tools, techniques, and best practices in data science, AI/ML, and big data technologies. 

Required Qualifications

  • Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
  • Technical Skills:
    • Proficiency in programming languages such as Python, R, and SQL.
    • Experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
    • Familiarity with data visualization tools/libraries (e.g., Tableau, Power BI, Matplotlib, Seaborn).

Preferred Skills

  • Knowledge of big data technologies (Hadoop, Spark) and cloud platforms (AWS, Azure, Google Cloud Platform).
  • Experience with MLOps practices and deploying models to production.
  • Background in domain-specific analytics (e.g., finance, healthcare, telecom) is a plus.
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