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.
Salary according to candidate qualification.