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Data Scientist en Madrid

Findasense

Lugar de trabajo
En sede
Horas
Full-Time
Prácticas
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Descripción de la oferta

Findasense is a fast-growing company. It has developed and deployed marketing and consumer interaction solutions to more than 40 markets . Since 2011, our team has doubled its size every year, and now comprises more than 250 full-time professionals. Findasense is fully aimed and committed to creating an outstanding, global and networked organization, with innovation, creativity and smart client service practices at the heart of all operations and capabilities. We seek for humble, talented, and ambitious people with strong ‘can-do’ and ‘start-up’ attitude.


MISSION

Our Data Scientist will collaborate with the data analysis team on developing new tools and getting insights whether from generated models output or from basic statistics or even from some wrangling data.

To keep a curious and skeptic spirit and being enthusiastic for learning about anything and finding ways to discover new methods and solutions.


ACCOUNTABILITIES

Requirements

Science or Technical Degree

Fully proficient in English and Spanish. Other languages are a plus.

Relational databases and no-sql databases.

Scripting Languages like R, Python,

Algorithms Optimization (Gradient Boost, AdaBoost, etc)

Matching Learning Algorithms (Classification and clustering)

Deep Learning Algorithms (DNN, RNN, CNN, LTSM, etc)

Experience on visualization frameworks and systems, e.g. Tableau, D3.js, etc.

Experienced designing and implementing products based on description, prediction and prescription


Cultural Fit

· Honesty.

· Relentlessly.

· Efficiency.

· Attention to detail.

· Analytical skills.

· Organization and planning.

· Fast Learning.

· Creativity and Innovation.

· Proactivity.

· Goal driven.

· Enthusiasm.

· High Standards.

· Communication Skills.

· Teamwork.

· Challenge willing.

Benefits

As a Findasense employee, your annual compensation package will include:

  • 23 days paid holidays per year.
  • Health Insurance.
  • Flexible job schedule.
  • Building data models with structured and unstructured data whether on databases or data-frames.
  • Building descriptive and predictive models from those data sets.
  • Developing new tools that help automate any task or make easier ways to extract and analyze data.
    1. Developing data science capabilities for multi-channel Digital Marketing (e.g. email, Facebook, Twitter, Instagram, etc), and any other Marketing Data Point as required.
    2. Designing social media monitoring algorithms (Sentiment analysis, Influencer analysis, Topic modeling and trend spotting) and scale them up towards real-time.
    3. Designing and developing algorithms and statistical models applied to our research marketing methodologies.
  • Defining guidelines to data treatment processes within company.
  • Mentoring team members and partners.


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