Role: Lead Data Scientist – Healthcare Analytics & Machine Learning
HRforGrowth® is engaged as the talent acquisition partner to conduct this search on behalf of a client organization that is hiring for this role. HRforGrowth is not the employer for this position. HRforGrowth identifies, evaluates, and presents top-tier candidates through its global talent acquisition practice; all employment decisions — including final selection, offer terms, compensation, and conditions of employment — are made solely by the hiring organization.
Our Client is seeking an experienced Lead Data Scientist to lead advanced data analytics, machine learning, and predictive modeling initiatives that support strategic and operational decision-making.
The Lead Data Scientist will work with complex structured and unstructured datasets, develop sophisticated analytical models, identify meaningful business insights, and translate complex analytical findings into clear, actionable recommendations for both technical and non-technical stakeholders.
This role will also provide technical leadership and mentorship to data science professionals while contributing to the continued development and advancement of the organization's data science capabilities
Location: Houston, Texas 77002
Job Type: Full-Time
Compensation: $108,000 – $136,000 per year
Important: Candidates must reside within approximately 20–30 miles of Houston, TX 77002.
This position is focused on advanced data science, machine learning, predictive modeling, statistical analysis, data mining, SQL, data visualization, and technical leadership. Healthcare industry experience is highly preferred.
Key Responsibilities
Data Science & Advanced Analytics
- Lead high-priority and complex data science initiatives with significant organizational impact.
- Analyze large, complex, structured, and unstructured datasets using advanced statistical and analytical techniques.
- Develop predictive models, algorithms, and data-driven solutions to address complex business challenges.
- Apply machine learning and statistical methodologies to business metrics and operational problems.
- Perform data mining, research, modeling, visualization, pattern analysis, and exploratory data analysis.
- Develop and test hypotheses and communicate analytical findings in a clear, concise, and actionable manner.
- Monitor, maintain, and evaluate existing analytical models, including model performance and goodness of fit.
- Identify opportunities to improve operational efficiency, productivity, scalability, and business outcomes through data.
Business & Cross-Functional Collaboration
- Collaborate with cross-functional teams to investigate and resolve complex data and analytical issues.
- Gather business and technical requirements and translate them into effective analytical solutions.
- Provide advanced data insights to support strategic planning and operational decision-making.
- Communicate complex analytical concepts and findings to both technical and non-technical audiences.
- Troubleshoot complex analytical and data-related challenges and recommend appropriate solutions.
Technical Leadership & Mentorship
- Provide technical leadership, coaching, and mentorship to other data scientists.
- Support training and knowledge-sharing initiatives related to data science methodologies, tools, and emerging technologies.
- Lead multiple projects simultaneously while managing priorities, timelines, and deliverables.
- Assist with the evaluation of data science vendors, technologies, platforms, and analytical tools.
- Contribute to the continued development and advancement of the organization's data science capabilities.
- Perform other related duties and projects as assigned.
Required Skills & Technical Expertise
- Advanced data science and analytics.
- Machine learning and predictive modeling.
- Advanced statistical analysis.
- SQL and database management.
- Data mining and data visualization.
- Structured and unstructured data analysis.
- Statistical modeling and hypothesis testing.
- Time-series forecasting and analysis.
- Regression analysis.
- Clustering and classification.
- A/B testing.
- Data storytelling and visualization.
- Business and technical requirements gathering.
- Project leadership and management.
- Cross-functional collaboration.
- Technical mentoring and team leadership.
- Advanced problem-solving and analytical reasoning.
- Executive and stakeholder communication.
Minimum Qualifications
Education
- Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or another related STEM field required.
- Master's degree in Data Science, Statistics, Computer Science, or a related field preferred.
Experience
- Minimum of 7 years of professional experience in Data Science.
- Strong experience with advanced analytics, statistical modeling, machine learning, and predictive modeling.
- Advanced SQL and database management experience.
- Strong programming skills and experience using statistical analysis and data science tools.
- Experience working with large, complex, incomplete, and/or unstructured datasets.
- Demonstrated ability to research, identify, and resolve complex data issues.
- Experience managing multiple data science projects and competing priorities.
- Strong ability to communicate complex analytical concepts and findings to both technical and non-technical audiences.
Machine Learning & Statistical Expertise
Candidates should have strong knowledge and practical experience with:
- Clustering techniques.
- Decision tree learning.
- Artificial neural networks.
- Classification techniques.
- Predictive modeling.
- Regression analysis.
- Statistical testing.
- Probability and statistical distributions.
- Hypothesis testing.
- A/B testing.
- Time-series analysis and forecasting.
- Model evaluation and performance measurement.
Preferred Healthcare Experience
Healthcare industry experience is highly preferred. Candidates with experience in one or more of the following environments are especially desirable:
- Hospital or healthcare data.
- Electronic Health Records (EHR).
- Healthcare Information Technology.
- Medical informatics.
- Healthcare finance.
- Revenue cycle analytics.
- Clinical analytics.
- Healthcare operational analytics.
Experience working with healthcare datasets, clinical systems, patient-related operational data, or healthcare financial and revenue-cycle information will be a strong advantage.
Professional & Leadership Competencies
The successful candidate will demonstrate:
- Exceptional analytical and problem-solving abilities.
- Strong mathematical and statistical reasoning.
- Strong project leadership and organizational skills.
- Ability to independently manage multiple projects and deadlines.
- Excellent written and verbal communication skills.
- Ability to translate complex analytical results into practical business recommendations.
- Strong collaboration skills across technical and business teams.
- Ability to mentor and guide other data science professionals.
- Ability to work effectively with minimal supervision in a fast-paced, multidisciplinary environment.
- Strong customer-service and stakeholder-management skills.
- Ability to handle challenging stakeholder situations and develop effective solutions.
- Commitment to accuracy, quality, continuous improvement, and data-driven decision-making.
Ideal Candidate Profile
The ideal candidate is a senior-level data scientist with 7+ years of hands-on experience in data science, advanced analytics, machine learning, statistical modeling, SQL, and predictive analytics.
Candidates who combine strong technical data science expertise with healthcare, hospital, EHR, medical informatics, or healthcare financial/revenue-cycle experience are particularly desirable.
The successful candidate will be comfortable leading complex analytical initiatives, working with large and incomplete datasets, mentoring other data scientists, collaborating with cross-functional stakeholders, and translating sophisticated analytical findings into practical business strategies and recommendations.
Work Environment
This is an on-site position in Houston, Texas, with local candidates preferred.
The role involves working with complex datasets, analytical tools, data science technologies, statistical models, and cross-functional business and technical teams.
Candidates should be located within approximately 20–30 miles of Houston, TX 77002 and be comfortable working in a fast-paced, multidisciplinary environment.
Compensation & Opportunity
- Annual Salary: $108,000 – $136,000.
- Full-Time employment.
- Leadership opportunity within an established organization.
- Opportunity to lead high-impact data science and analytics initiatives.
- Exposure to advanced machine learning, predictive modeling, and statistical analysis.
- Opportunity to mentor and develop other data science professionals.
- Opportunity to contribute to strategic and operational decision-making through advanced analytics.
Additional Requirements
- Must be legally authorized to work in the United States.
- Candidates must be located within approximately 20–30 miles of Houston, TX 77002.
- Must be willing to work on-site in Houston, Texas.
- Ability to manage multiple data science projects and competing priorities is essential.
- Strong communication skills and the ability to work with both technical and non-technical stakeholders are required.
Why Join?
This is an excellent opportunity for an experienced Lead Data Scientist to take a leadership role in advanced analytics, machine learning, predictive modeling, and data-driven decision-making.
The successful candidate will have the opportunity to lead complex analytical initiatives, influence strategic and operational decisions, mentor other data science professionals, and help advance the organization's overall data science capabilities.
Candidates with healthcare, hospital, EHR, medical informatics, clinical analytics, healthcare finance, or revenue-cycle experience will have an opportunity to apply their technical expertise to meaningful healthcare-related business and operational challenges.
About HRforGrowth:
HRforGrowth is a full-service HR and talent partner built to support companies that are scaling, transforming, or navigating change. HRFG is globally recognized for delivering quality, speed, and cost-effective talent solutions across every level of the workforce. Through its global talent acquisition practice, HRforGrowth applies world class rigor and precision to identifying exceptional professional and executive talent on behalf of its clients — from temporary staffing to permanent hourly workers through to placing C-suite executives. HRforGrowth is presenting this opportunity in its capacity as the retained search partner and does not serve as the employer of record for this position.
Equal Employment Opportunity:
In its recruiting and search practices, HRforGrowth does not discriminate on the basis of race, color, religion, national origin, age, marital status, physical or mental disability, sex, sexual orientation, gender, or gender identity, and welcomes applications from all qualified individuals. HRforGrowth evaluates and presents candidates to its clients without regard to any protected characteristic.
HRforGrowth endeavors to advise the hiring organization to comply with all applicable federal, state, and local equal employment opportunity laws — including those enforced by the U.S. Equal Employment Opportunity Commission (EEOC) — in its hiring decisions, terms of employment, and workplace practices.
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