Description tasks and responsibilities of the position:
- Responsible for obtaining knowledge and value from data, using Big Data analytical techniques and technologies.
- Solid knowledge of computer science, statistics and mathematics.
- Able to identify and analyze the business requirements of the project.
- Performs Data Manipulation and Data Quality tasks.
- Able to identify Datasets, and debugs the structure to facilitate analysis.
- Design and build analytical models for pattern discovery, calculation of scorings, behavioral analysis, identification of relationships between entities, segmentations, etc.
- Train, develops and refines the analytical model to obtain the most accurate model.
- Analyzes and interprets results in key business.
- Make reports and advanced visualizations of the main conclusions.
Essential technical requirements:
- Experience analyzing data in Big Data Systems (at least 1): Hadoop, Spark.
- Programming Languages (at least 1): Python, R, Scala.
- Data Manipulation (at least 2): SQL, Hive, Pig, Impala, SparkQL, Sqoop, Flume, Web Scraping.
- Statistical Algorithms & Machine Learning: correlation, regression, forecasting, time-series, classifiers, clustering.
Assessable technical requirements:
- Programming Languages: Any addition to the above, plus Julia and Java.
- NoSQL systems: MongoDB, Cassandra, CouchDB, Redshift, etc.
- Display: Gephi, Neo4j, graphics bookcases in R and Python, Kibana, Visual.ly, D3.js, QlikView, Tableau, CartoDB, etc.
- Text Mining: Elasticsearch, Lucene, Solr, etc.
- Analytical Tools and Data Mining: KNIME, RapidMiner, SPSS, SAS, Statistica, MATLAB.
- Other Big Data technologies: Logstash, STORM, Kafka, etc.
- Experience program against third-party APIs.
- Degree in Mathematics, Computer Engineering, Higher Engineering or Physics.
- Double degrees will be evaluated in any of the above degrees and doctorates or Masters in Artificial Intelligence, Mathematics, Computer Science or Statistics.
- Publications and papers related to data analytics and Artificial Intelligence will be evaluated.
- Courses and certifications in any of the Big Data ecosystem technologies and handling techniques and data analysis will be evaluated.
Years of experience in a similar position:
- 2-3 years in data analytics projects that have used Big Data systems and technologies. Ideally in private enterprise.
- Projects that have been analyzed large volumes of data from heterogeneous sources will be specially evaluated.
- Academic research projects will be evaluated.
- Results orientation
- Analytical thinking.
- Fluent English
- Knowledge of the financial sector will be appreciated and in general, any experience in analytical data and projects in Banks and Insurance.
- Permanent contract
- Flexible working hours
- Modern tech stack
- Casual dress code
- Friendly and international team
- English classes
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