data scientist Resume Examples

You may be a wizard at visualizing data in Splunk or working with MongoDB databases. You might have experience in developing APIs in REST, and maybe you’ve even completed your degree. However, even with all your technical expertise, it can be tough to land a new job without a strong data scientist resume. Writing a resume can be intimidating whether you have years of experience or are just starting your career. It needs to let recruiters and hiring managers quickly see your experience in statistical analysis, predictive modeling, and previous work with large-scale data sets. Your resume should highlight your education and any technical certifications you’ve achieved as well. We are here to help you. By following our professional resume example tips and templates, we will guide you in creating an easy-to-scan document that tells a recruiter or hiring manager that you are a great candidate for the job. With our professional tools, you will be one step closer to getting a job interview.
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Related Resumes & Cover Letters

1

data scientist

  • Scraped data from real estates sources
  • Built outlier detection, clustering models
  • Created model for buy/rent price prediction
  • Prepared R shiny web application for model usage
2

data scientist

  • Handled design, modelling and deployment for a NLP project to automate resume parsing. 
  • Developed case study on Attention Models and SOTA architecture BERT
  • Developed various Machine Learning, Deep Learning and Artificial Intelligence activities as part of the course material
  • Taught lectures to nearly 100 professionals in the range 0-25 years of experience.
3

data scientist

  • Used data mining and data cleaning techniques to analyze job posting descriptions
  • Used Python to parse keywords from a self-created dictionary to determine specific trends in Computer Science jobs such as popular programming languages, more need for soft skills, etc.
  • Performed Machine Learning algorithms (Linear Regression, Clusters) to determine future trends in the field
  • Experienced using many Python Data Science and Machine Learning libraries such as Pandas, Numpys, Seaborn, Scikit Learn and Matplotlib
4

data scientist

  • Build Attribution and Prediction Models using Time Series , Regression and other Machine Learning techniques to support the IB research analysts
  • Build R Shiny applications- For Campaign Analytics, Data Quality Monitoring – which results into efficient functioning and time saving
  • Survey Analysis using bespoke analysis methodologies
  • Optum Deep Vision(Intelligent Character Recognition):
5

data scientist (stage)

  • Etude des mécanismes de transparence publicitaire de Facebook et de Twitter.
  • Développement d’une plateforme pour l’audit des annonces publicitaires fournis par les médias sociaux.
  • Développement d’un outil de visualisation des données et Analyse statistique des annonces
  • Platform lead for 3 of the company’s software development projects involving SQL Server, MySQL and ParAccel (Actian Matrix) 
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