Data Scientist

We are looking for a Data Scientist to join a healthcare-focused analytics team in Texas, where you will turn complex data into practical insights and scalable solutions. This contract position with the potential to become permanent is ideal for someone who combines strong statistical knowledge with curiosity, business acumen, and a passion for solving meaningful problems. You will work closely with technical and business partners to design predictive models, improve data quality, and communicate findings that support informed decision-making.

Responsibilities:
• Transform large, complex datasets into actionable insights by exploring trends, identifying patterns, and uncovering opportunities that support business goals.
• Build, test, and refine machine learning models and predictive solutions that improve decision-making and deliver measurable value.
• Prepare structured and unstructured data for analysis through cleansing, validation, and preprocessing to ensure reliability and usability.
• Strengthen data acquisition practices by recommending improvements that capture the information needed for advanced analytics initiatives.
• Partner with business leaders, analysts, and IT teams to define problems, evaluate options, and shape data-driven strategies.
• Communicate analytical findings through clear narratives, presentations, and visualizations that make complex results easy to understand.
• Create impactful dashboards and visual tools that highlight performance gaps, emerging opportunities, and areas for operational improvement.
• Facilitate discussions with stakeholders to gather requirements, iterate on analytical approaches, and align solutions with business needs.
• Handle sensitive information with discretion while supporting a culture of continuous improvement, accountability, and evidence-based decision-making.

Requirements

• Bachelor’s degree in Information Systems, Data Science, Mathematics, Statistics, Computer Science, or a related field, along with at least 5 years of experience in data and analytics; an equivalent combination of education and experience may also be considered.
• Strong programming ability in Python and experience with statistical or data processing languages such as R, SQL, Hive, or Pig.
• Demonstrated knowledge of machine learning techniques and predictive modeling methods, including classification and pattern detection approaches.
• Solid foundation in applied statistics, including regression, probability distributions, hypothesis testing, and estimation methods.
• Strong mathematical background with working knowledge of linear algebra and multivariable calculus.
• Experience with data wrangling, data mining, and preparing messy or incomplete datasets for meaningful analysis.
• Ability to present technical concepts clearly to non-technical audiences and work effectively with stakeholders across multiple teams.
• Comfortable working with confidential information and operating in a regulated environment such as healthcare, insurance, or social services.