Launchpad.AI

Become a Data Scientist

Immersive, hands-on training for Vodafone employees

 
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Become a Data Scientist!

Hands-on Training Program for Vodafone Employees

The role of Data Scientist has been called the "sexiest job of the 21st century" by the Harvard Business Review. Vodafone wants to invest in you and prepare you for the future by developing your skills to become one!

We’re looking for people with a passion for Data Science or Machine Learning to join an intense 8-week training course in Madrid. This is a once-in-a-lifetime opportunity to gain Vodafone's sponsorship and learn from Silicon Valley trainers - whose mission is to develop the world's Data Science talent and grow the international Machine Learning community.

This training is the first of its kind at Vodafone, bringing unique advantages and opportunities to early adopters: enabling access to world-class knowledge in Data Science and Artificial Intelligence and how to apply it to real, business-facing projects.

Are you up for the challenge? Are you motivated to drive the future of Big Data within Vodafone as a Digital Telco? Places are limited, so act now to take advantage of this offer to secure a place in our global Data Science community.

Read on to find out more and to apply now!

 

Our Passion for Diversity

Network/Software Engineers, Business and Finance Analysts, Scientists, Everyone with a Passion to Learn

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Program

The course will run for 8-weeks at the Vodafone Campus, Madrid, Spain.

The majority of the time is spent pair programming.  We try to pair participants more proficient in quantitative skills with participants more proficient in software development.

We use Agile processes with daily scrums and a variety of collaboration tools including Slack, Github and Trello. We also have a weekly retrospective and iteration planning.

Content

  • Basic framing of problems to be solved through machine learning including selecting input features, avoiding bias and interpreting model feature importance

  • Exploratory data analysis including statistical summaries and visualizations with plotting libraries like Matplotlib and Seaborn.

  • Feature engineering from raw data using tools like Pandas, NumPy and other Python and Linux command-line libraries

  • Model training / selection process and hyper-parameter tuning

  • Visualizing of model results

  • Placing models into production

  • Tools include: Scikit-Learn, Pandas, NumPy, Seaborn, Word2vec, fastText, Keras, XGBoost


Who we’re looking for

Unless specifically invited, you must currently be a Vodafone employee based in Spain.

We’re looking for individuals with the following attributes:

  • Intellectual: A deep interest in solving problems and puzzles, intellectual curiosity, and a voracious appetite to learn

  • Technical: Statistics, programming, social science, math, computer science, software development, physics, engineering or related background

  • Professional: Ambition to make a business impact and drive commercial results

  • Leadership style: Team spirit and collaboration, as well as willingness and ability to mentor

  • Mind-set: Analytical and creative, but also practical and focused on tangible outcomes

Suitable backgrounds include, but are not limited to:

  • Software engineers

  • Business and finance analysts

  • Scientists and/or physical science backgrounds

  • Network engineers that can code

Required capabilities:

  • Creative problem-solving ability

  • Basic coding proficiency (particularly in Python)

  • Foundational understanding of machine learning theory and methods and a basic understanding of the concepts involved:

    • Supervised vs Unsupervised Learning

    • Classification

    • Regression

    • Dimensionality Reduction and Optimisation

Some exposure to coding and associated methodologies is critical to success!

We will also consider anyone who can demonstrate appropriate skills and aptitudes used outside of the workplace. For example:

  • A user of data and analytics programs like SAS or SPSS

  • Those who carry out modelling or use macros in Excel

  • Those with technical experience where coding or coding-like work is part of the skill set


You will gain

  • Eight weeks of intensive training and development

  • Hand-on experience working in a particular area of machine learning, to solve a specific business problem

  • A wide range of high-value machine learning solutions and agile software-development principles

  • Cutting edge deep learning and large-scale optimisation techniques to computer vision, natural language processing and time-series problems

  • The opportunity to become part of an international centre of expertise for data science and analysis


Your commitment

Since the program will be free to participants, you must commit to:

  • Being in the program full time for entire duration (this is a real program, with a heavy workload, homework, exams, quizzes, and evaluations)

  • Basing yourself in Madrid for the 8-week duration of the course

  • Mentoring other trainees for 6 months after program completion

  • Signing the High Spend Training Claw Back Policy (we will send a copy of this to you should you be accepted)

  • Serving as ambassadors for Big Data and machine learning and continuing to educate our organisation

  • During and after the program, complying with the Big Data code of ethics


Application Process

After you submit the application, your first step is to complete one of the challenge problems. You don’t need previous machine learning experience or exposure to any of these challenge topics beforehand, but you will need to show aptitude for problem solving and rapidly acquiring and demonstrating new skills. This, above all other qualifications, is your opportunity to demonstrate your aptitude for the program!

After you have completed and shared your challenge, you will need to book yourself into a 30-minute interview slot. We will notify you via e-mail regarding your acceptance. You will then need to coordinate travel and living arrangements for the duration of the program according to your local policies.