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Skills

  • Customer service
  • Statistical analysis
  • Adaptability in Fast-paced Environments
  • Hypothesis testing
  • A/B testing
  • API integration for data extraction
  • Analytical problem-solving skills
  • Cross-functional teamwork
  • Insurance billing
  • Supervision

Work Experiences

  • Automated data retrieval and analysis pipelines through Python scripts, reducing manual report generation time by 59%.
  • Boosted inventory optimization.
  • Cleaned and pre-processed datasets containing more than 12 million rows, improving model accuracy by 78% points.
  • Aligned data science projects with company goals.
  • Analyzed customer behavior data.
  • Increased customer satisfaction by coming up with new ways to solve problems.
  • Finished standard of project, which resulted in framework.
  • Worked with others to brainstorm new category possibilities.
  • Provided excellent service and attention when dealing with customers face-to-face or over the phone.
  • Cleaned and pre-processed datasets.

Summaries

  • Ability to recognize system issues and integrate metric solutions to achieve system.
  • Actively seeking opportunities to drive growth at Cedar Works.
  • Strong technical skills and experience in budget management.
  • Data analysis Committed to identifying and leveraging opportunities for growth, with a proven ability to build effective teams.
  • Junior Data Scientist with workflow optimization and vendor management abilities.
  • Adept at developing machine learning solutions for churn prediction. Achieved a 85% reduction in churn through advanced customer retention models. Excited about scaling similar results at Brightline.
  • Proficient in promoting process by leveraging budget management and cross-functional collaboration knowledge.
  • Looking forward to taking on a new challenge with a successful team.
  • With hands-on experience, eager to learn new skills and advance knowledge.
  • Aiming to apply my skills in a challenging environment.

Accomplishments

  • Developed a real-time anomaly detection system that caught potential fraud cases in financial data for Ironclad Systems.
  • Enhanced sales prediction models by implementing advanced feature scaling techniques, yielding a 57% improvement in accuracy.
  • Implemented version control on data science experiments using Git, streamlining collaboration with the team and reducing redundant work.
  • Led feature selection process for a classification model, improving accuracy by 71% using category.
  • Carried out data extraction, transformation, and loading (ETL) tasks for system, resulting in a 73% speed improvement in report generation.
  • Designed an automated data pipeline using Workday, reducing data processing time from 5 hours to 8 minutes.
  • Presented key findings to stakeholders and influenced business strategy adjustments, driving a revenue increase of $12 over 10 months.
  • Collaborated with operations to build exploratory data visualizations, influencing decision-making for metric and achieving initiative.
  • Identified the most impactful factors related to customer churn using correlation analysis, reducing churn rates by 75%.
  • Executed predictive analytics on sales data, improving forecast accuracy by 67% through advanced regression models.

Affiliations

  • Graduate Fellow, process Research Fellowship - Conducted supervised research on predictive models in the domain of business intelligence and customer satisfaction.
  • Volunteer Data Scientist, Open Data Science Projects - Contributed to community-driven data science projects related to public health, environmental causes, and more.
  • Contributing Member, PyData Network - Collaborated on open-source projects related to data manipulation, analysis, and visualization using Python's data science stack.
  • Organizer, Data Science Meetup Group in Raleigh - Facilitated monthly meetings focusing on data science, artificial intelligence, and innovations in analytics.
  • Member, International Machine Learning Society (IMLS) - Engaged with professional machine learning researchers and practitioners to discuss cutting-edge algorithms and cloud implementation strategies.
  • Graduate, procedure Data Science Master's Program - Specialized in data mining, big data handling, and predictive analytics for industry use cases.
  • Collaborator, Kaggle Competitions - Contributed to multiple data science challenges, achieving top 77% rankings in classification and regression tasks.
  • Member, Association for Computing Machinery (ACM) - Engaged in discussions and research around computational models and data science applications in industry.
  • Attendee, Neural Networks and Deep Learning Conference, 2017 - Gained insights from experts on state-of-the-art neural network architectures and unsupervised learning.
  • Researcher-in-training, process AI Lab - Led research on reinforcement learning algorithms with applications in real-world scenarios such as automation and robotics.

Certifications

  • HarvardX: Data Science Professional Certificate by edX
  • Certified Python Programmer by PCEP
  • Certified Data Scientist (CDS) by Data Science Council of America (DASCA)
  • Coursera Machine Learning Specialization by Stanford University
  • Professional Certificate in Data Engineering from AWS Academy
  • Project Management Professional (PMP)
  • CompTIA Security+
  • TensorFlow Developer Certificate
  • First Aid/CPR
  • Microsoft Certified: Azure Data Scientist Associate

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