Title: Python Data Science Engineer

Location: Plano, TX

Duration: 12 months

Salary Range: $60-$65 per hour 

What we’re looking for

• This role is ideal for someone who thrives at the intersection of computational science, data analysis, and business consulting.
• The ideal candidate will excel in manipulating, analyzing, and cleaning data, using predictive and prescriptive models to extract actionable insights that inform business decisions.
• They should also be proficient in programming with Python, leveraging it to build robust models and ensure seamless deployment from development to production.
• The ability to present results and recommendations effectively to business partners and leaders is essential.

What you’ll be doing

• Work closely with team members and business partners to identify and prioritize key questions and drive impactful data-based decisions. 
• Extract, manipulate, and clean data from diverse sources using SQL and Python, preparing it for detailed analysis and model development. 
• Develop and implement sophisticated predictive and prescriptive models using statistical and machine learning techniques.
• Ensure these models address key business challenges and deliver actionable insights. 
• Create clear, compelling data visualizations to effectively communicate findings to both technical and non-technical stakeholders. 
• Effectively and efficiently transition models from development to production within the organization’s existing cloud ecosystem.
• Software development with a Python environment
• Participate actively in project planning and prioritization sessions to ensure data initiatives align with business goals. 
• Stay updated with the latest industry trends and tools and integrate this knowledge to improve methodologies and solutions.

Requirements:

• Master’s degree or higher in a relevant analytical field. 
• Highly proficient with SQL
• Hands-on experience with software development using Python Pandas, and Numpy
• Experience solving problems using a variety of statistical and machine learning techniques. 
• Hands-on experience using statistical or machine learning frameworks to solve a variety of real-world problems (e.g., statsmodels, scikit-learn, PyTorch, TensorFlow, etc). 
• Knowledge of methods like Logistic Regression, Time Series Analysis, GLMs, Mixed Modeling, Multivariate Statistics, Predictive Modeling, Decision Trees, Gradient-Boosted Trees, Random Forests, and Neural Networks. 
• Proactive approach to identifying problems and developing innovative solutions.
• Experience with version control in GitHub

Added bonus if you have (Preferred):           

• Familiarity with CI/CD practices to streamline model deployment and code management. 
• Hands-on experience with cloud-based machine learning platforms (e.g., AWS SageMaker or Azure ML) to leverage scalable computing resources and tools. 
• Demonstrated ability to lead through influence, effectively navigating and prioritizing complex cross-departmental projects to drive impactful change. 
• Capability to replace and bridge existing legacy infrastructure and processes. 
• Experience with the Snowflake, Netezza, or MS SQL environment
• Experience with SAS programming language
• Understanding of cashflow financial analysis and its implications for business strategy is highly desirable