Find Your Next Data Scientist: Meet & Greet

Washington, D.C. campuses

GA D.C.
1133 15th Street NW, 8th Floor
Washington D.C. 20005

Past Locations for this Event

Find Your Next Data Scientist: Meet & Greet

Washington, D.C.

Washington, D.C. campuses

GA D.C.
1133 15th Street NW, 8th Floor
Washington D.C. 20005

Past Locations for this Event

About this event

Looking for talented Data Scientists to join your team in 2019? Look no further

General Assembly London welcomes you to meet the recent graduates of our Data Scientists Immersive Programmes.

Think of it like a reverse job fair, where our graduates - who've successfully finished their 3-month immersive courses - will be showcasing their projects and portfolios, ready to talk to you about opportunities within your team.

Our graduates have gone on to successful careers at global brands, award-winning agencies, and high-growth startups, including BBC, ASOS, Sky, Government Digital Service (GDS), Selfridges, Expedia, The Trainline, Red Badger, The Telegraph, Duedil, GTB, +rehabstudio, AKQA, Microsoft, American Express, and hopefully yours.

Bonus! Hiring GA talent is at no cost to you. Can't make the event? Check out our graduate profiles online here: http://generalassemb.ly/talent


Takeaways

Read on for more information about our graduates...

All our students have experience working with agile methodologies, and utilising stand-ups as a way to increase performance.

MEET JUNIOR DATA SCIENTISTS WHO CAN:

  • Collect, extract, query, clean, and aggregate data for analysis using SQL and Unix commands, Python (Pandas), and do data cleaning/data munging. Perform exploratory data analysis using Python stack including - but not limited to - Pandas, SciPy, Sklearn and Ipython (Jupyter) and doing feature extraction and selection.
  • Build, implement, and evaluate data science problems using appropriate machine learning models for regression and classification. such as Linear Models, SVMs, Decision Trees, Ensemble Models (Random Forest, Bagging, Boosting) and KNN. Also demonstrate knowledge of Clustering (K-means and Hierarchical clustering), NLP and Time series analysis.
  • Use appropriate data visualisation tools such as matplotlib, seaborn and Tableau, and using iPython notebook.
  • Identify and solve big data problems using Hadoop/MapReduce, Apache Spark, and the AWS stack (EC2 and S3).

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