[Your Full Name]
[Your Phone Number] | [Your Email] | [City, State]
LinkedIn: [Your LinkedIn URL]

PROFESSIONAL SUMMARY
Data Science Consultant with [X] years delivering ML solutions across [industries]. Expert in translating business problems into technical solutions and communicating insights to C-level executives. Proven ability to manage multiple client engagements simultaneously and drive measurable business impact.

TECHNICAL SKILLS
Programming: Python, R, SQL
ML/Analytics: Scikit-learn, TensorFlow, XGBoost, Statistical Modeling, Forecasting
Consulting Tools: PowerPoint, Excel, Tableau, Power BI
Cloud: AWS, GCP, Azure
Industries: [Finance, Healthcare, Retail, Manufacturing, etc.]
Methodologies: Agile, Design Thinking, Lean Analytics

PROFESSIONAL EXPERIENCE

Data Science Consultant / Senior Consultant
[Consulting Firm Name], [City, State]
[Start Date] – Present
• Lead data science engagements for [number] clients across [industries] generating $[amount]M in value
• Manage project lifecycle from scoping and proposal to delivery and handoff
• Develop predictive models, recommendation systems, and forecasting solutions
• Present findings and recommendations to C-suite executives and stakeholders
• Mentor junior consultants on technical and client management skills
• Contribute to business development through proposal writing and client presentations

Selected Client Engagements:

[Industry] Client: Revenue Optimization
• Challenge: Client losing market share with declining margins
• Approach: Built dynamic pricing model using [techniques]
• Impact: Increased revenue by [X%] ($[amount]M) while improving margins by [Y%]
• Duration: [X] months | Team: [Y] consultants

[Industry] Client: Customer Analytics
• Challenge: High churn rate and poor understanding of customer segments
• Approach: Developed churn prediction model and segmentation analysis
• Impact: Reduced churn by [X%] saving $[amount]M annually
• Duration: [X] months | Team: [Y] consultants

[Industry] Client: Operational Efficiency
• Challenge: Inefficient supply chain with high carrying costs
• Approach: Built demand forecasting model with inventory optimization
• Impact: Reduced inventory costs by [X%] ($[amount]M) while maintaining service levels
• Duration: [X] months | Team: [Y] consultants

Data Scientist
[Previous Company/Firm], [City, State]
[Start Date] – [End Date]
• Supported [number] consulting projects across [industries]
• Developed ML models and conducted advanced analytics
• Created client-facing presentations and dashboards
• Collaborated with cross-functional teams including strategy, engineering, and design

EDUCATION
[Master's or Bachelor's], [Field]
[University Name], [City, State]
Graduation: [Year]

CERTIFICATIONS
• [PMP or Agile Certification], [Year]
• [Cloud Certification], [Year]
• [Industry-specific certification], [Year]

CONSULTING SKILLS
• Client Management: Build relationships, manage expectations, handle difficult conversations
• Project Management: Scope definition, timeline management, stakeholder communication
• Business Acumen: Understand P&L, market dynamics, competitive landscapes
• Presentation: Storytelling with data, executive communication, workshop facilitation
• Adaptability: Quick learning across new industries and business contexts
• Team Leadership: Manage junior consultants, delegate effectively, provide feedback

PUBLICATIONS & THOUGHT LEADERSHIP
• [White Paper or Article Title], [Platform], [Year]
• [Conference Presentation], [Event Name], [Year]