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Skills

  • Root cause analysis
  • ETL processes
  • Communications
  • Project organization
  • Developing software applications
  • Operational improvement
  • Identifying trends
  • Data Modeling
  • Adaptability in Fast-paced Environments
  • Data-driven decision making

Work Experiences

  • Achieved a 41% uplift in accuracy.
  • Assisted in the deployment of an interactive dashboard.
  • Automated data retrieval and analysis pipelines through Python scripts, reducing manual report generation time by 59%.
  • Answered 9 phone calls per several months to assist customers.
  • Cleaned and pre-processed datasets containing more than 12 million rows, improving model accuracy by 78% points.
  • Developed a reputation for punctuality and hard work.
  • Cleaned customer behavior data.
  • Was in charge of the initiative team's databases.
  • Kept my method knowledge up to date by doing process improvement and strategic planning.
  • Built and deployed machine learning models for category, reducing customer churn by 35% within 18 months.

Summaries

  • Aiming to lead innovative projects at Ironclad Systems.
  • Junior Data Scientist and team leader with 16 years of experience in initiative settings.
  • Knowledge of QuickBooks in depth, as well as client relations and risk assessment abilities.
  • Results-oriented Biotechnology professional with strategic planning, process improvement, and cross-functional collaboration strengths.
  • Active leader with excellent communication and collaboration skills.
  • With a team-oriented mentality, highly organized, proactive, and punctual.
  • Lean certified
  • Achieved 47% improvements in customer engagement rates.
  • With hands-on experience, eager to learn new skills and advance knowledge.
  • SAP and Jira experts with exceptional interpersonal skills.

Accomplishments

  • Engineered features for a time-series forecasting model that improved demand prediction accuracy for Microsoft Excel by 63%.
  • Developed a machine learning solution that predicted product demand for Salesforce, reducing manufacturing excess by 42%.
  • Applied unsupervised learning to categorize unstructured data, uncovering hidden patterns and leading to a standard increase.
  • Trained and validated deep learning models on image data, achieving a 75% accuracy boost in image classification for process.
  • Implemented version control on data science experiments using Git, streamlining collaboration with the team and reducing redundant work.
  • Reduced project delivery time by automating data cleaning processes using Salesforce, leading to a 81% improvement in overall team productivity.
  • Built a segmentation model which classified customers into 16 personas, enabling targeted marketing strategies and increasing ROAS by 53%.
  • Developed a sentiment analysis model on customer feedback, contributing to a 67% increase in customer satisfaction.
  • Spearheaded the migration of machine learning workflows to a cloud platform, resulting in 76% reduction in compute costs.
  • Executed predictive analytics on sales data, improving forecast accuracy by 67% through advanced regression models.

Affiliations

  • Graduate, procedure Data Science Master's Program - Specialized in data mining, big data handling, and predictive analytics for industry use cases.
  • Contributor, TidyTuesday (#tidytuesday) - Participated in weekly social data projects focused on exploring and visualizing datasets using tidyverse tools.
  • 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.
  • Participant, process Data Science Bootcamp - Completed an intensive hands-on training in statistical analysis, machine learning, and data visualization.
  • Participant, Data Science for Social Good Fellowship - Contributed to public-good data science projects, using machine learning algorithms to address socio-economic issues.
  • Member, Big Data Institute - Regularly collaborates with peers on topics such as distributed computing, database architecture, and parallel data processing.
  • Certified SQL Specialist, Brightline - Displayed expertise in database management, query optimization, and performance tuning for large-scale datasets.
  • Collaborator, Kaggle Competitions - Contributed to multiple data science challenges, achieving top 77% rankings in classification and regression tasks.
  • Member, The Royal Statistical Society - Maintained a professional focus on hypothesis testing, predictive modeling, and statistical proofs.

Certifications

  • Cloudera Certified Data Scientist CCDS
  • Association for Project Management (APM)
  • Google Professional Data Engineer
  • Microsoft Certified: Azure AI Engineer Associate
  • Databricks Certified Associate ML Practitioner
  • Postgraduate Diploma in Data Science (PGDipDS) by Meridian
  • Tableau Desktop Specialist Certification
  • TensorFlow Developer Certificate
  • Graduate Certificate in Big Data by framework
  • SAS Certified AI & Machine Learning Professional

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