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Skills

  • Multivariate Testing
  • Cloud computing platforms (e.g., AWS, Azure)
  • Operational improvement
  • Customer service
  • KPI Development and Monitoring
  • Process improvement
  • Problem resolution
  • Data visualization (e.g., Tableau, Power BI)
  • Organization
  • Data governance and compliance

Work Experiences

  • Audited large datasets for compliance.
  • Cleaned and pre-processed large datasets.
  • Analyzed competitor metrics.
  • Achieved a 74% shorter time-to-market.
  • Used a variety of computer languages and procedures to perform systems and data analysis.
  • Decided on methods and criteria for evaluating warehouse data.
  • Collaborated with operations to build predictive models that allowed for forecasts with 60% accuracy during 2016.
  • Avoided penalties of up to $16.
  • Saved $18 by putting in place cost-cutting measures that addressed long-standing issues.
  • Analyzed historical data.

Summaries

  • Costs were consistently reduced while profits were increased.
  • Collaborated with cross-functional teams.
  • Adept at using Python for statistical models.
  • Effectively collaborates with multi-functional roles to identify and leverage areas for data system improvement.
  • Confident Data Analytics Intern skilled at improving marketing strategies through strong analytics and client segmentation practices, boosting overall sales by $7 in 2020.
  • Achieved forecasting accuracy of 38%.
  • Achieved metric improvement of 18%.
  • Adept at using Python and R.
  • Adaptable Data Analytics Intern.
  • Excellent track record of resolving issues, increasing customer satisfaction, and driving overall operational improvements.

Accomplishments

  • Assessed ROI of marketing strategies, leading to a 57% increase in cost efficiency across platforms.
  • Automated resource-intensive reporting processes, reducing report generation time by two years for marketing.
  • Developed predictive models to streamline inventory management, reducing overstock by 57% and minimizing waste.
  • Evaluated A/B testing results and provided actionable recommendations, leading to a 36% increase in campaign success rate.
  • Partnered with marketing to refine customer segmentation strategies, increasing personalized marketing efforts by 62%.
  • Utilized customer segmentation techniques to optimize targeting in email campaigns, boosting conversion rates by 82%.
  • Led initiatives to improve user surveys, raising response rates by 38% and enhancing customer feedback quality.
  • Researched external data sources to enrich market trend analysis, influencing product development strategies and increasing market competitiveness.
  • Tracked KPIs and generated daily reports that presented insights on operational performance to senior management.
  • Analyzed historical time series data to forecast customer behaviors, enabling proactive marketing strategies.

Affiliations

  • Society of Women Engineers
  • Affiliate with method AI & Machine Learning Research Association
  • Jaycees
  • Alumni of Google Data Analytics Professional Certificate 2022
  • Enrolled in Harvard’s Professional Development Program in Data Science
  • Member of International Institute of Business Analysis (IIBA)
  • Project Management Institute
  • Association of Information Technology Professionals
  • Member of local Python User Group and attend monthly hackathons
  • Active participant in 'Women in Data Science' (WiDS) regional events 2023

Certifications

  • Google Certified Professional Cloud Architect
  • Advanced SQL for Data Scientists (DataCamp, 2017)
  • Certified Business Intelligence Professional (CBIP)
  • SAS Certified Specialist: Base Programming Using SAS 9.4
  • Post Graduate Program in Data Science (Purdue University & Simplilearn)
  • Excel to MySQL: Analytic Techniques for Business by Duke University on Coursera
  • IBM Data Science Professional Certificate
  • Introduction to Data Science in Python (University of Michigan on Coursera, 2015)
  • Certified Business Analysis Professional (CBAP)
  • Salesforce

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