CX Intelligence Specialist, Innovation Leader




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

Relational databases and no-sql databases.

Scripting Languages like R, Python, Java, C++, C# or PHP.

DataBase languages like SQL, NoSQL, PostgreSQL, etc.

Good knowledge on statistics.

Social network analysis.

Machine learning and supervised (regression, classification…)/unsupervised models (clustering, dimensionality reduction…)

Knowledge of Machine Learning

Knowledge of MapReduce concepts and architectures and File Systems such as HDFS.

Good capability for complex analysis and synthesis.

Social Web APIs programming.

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

Experience with xaaS, like AWS, MS Azure, etc.

Rigorous and strict enough to follow methodic working lines.




Findasense is a fast-growing company. It has developed and deployed marketing and consumer interaction solutions to more than 40 markets over the last 4 years. 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 love humble, talented, and ambitious people with strong ‘can-do’ and ‘start-up’ attitude.

Imagine a place where you work hand to hand with your client and team within a high creative environment.


Mission:

Our Intelligence Specialist 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.

Outcomes and accountabilities:

  1. Building data models with structured and unstructured data whether on databases or data-frames.
  2. Building descriptive and predictive models from those data sets.
  3. 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.
  4. Defining guidelines to data treatment processes within company.
  5. Mentoring team members and partners.



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