Data Scientist II
- Centro Corporativo El Cafetal, Heredia, Heredia, Costa Rica
- Department: Analytics
- Role Type: Hybrid
- Employee Status: Regular
- Schedule: Full Time
- Shift: Day Shift
Experian is the world’s leading global information services company, unlocking the power of data to create more opportunities for consumers, businesses and society. We are thrilled to share that FORTUNE has named Experian one of the 100 Best Companies to work for. In addition, for the last five years we’ve been named in the 100 “World’s Most Innovative Companies” by Forbes Magazine. With a focus on our employees, we have been certified for the third time as Great Place To Work (GPTW). Experian Consumer Information Services is redefining the way our clients do business within all aspects of the customer credit lifecycle. Fueled by best-in-class data and innovative technology we help businesses make smarter decisions, identify consumers, make decisions on loans, market to prospects and collect.
Are you fascinated by machine learning and data science? Would you like to join an emerging team focused on operational analytics in a growth company with an amazing culture?
If so, we have an opportunity for you to use your analytical skills to convert data into predictive insight and meaningful information that enables business process improvement. Come be part of a Data Enrichment team that leads the creation and implementation of new models/processes that bring measurable quality improvement to the Experian BIS Commercial Data Repository.
What you´ll do:
- Create and implement machine learning models to improve data quality in a production environment.
- Own and iterate on previously created models
- Design, build and maintain
- Documentation of model performance and features
- Collaborate with technology and other business teams
- Continual learning of new technologies and data science
- Data visualization of performance metrics
What your background looks like:
- 2+ years of working experience in data model development and implementation
- Ability to independently support existing products
- Experience with supervised machine learning methods and concepts
- Experience in implementing a ML solution into a production environment
- Proven ability to work on models with large, complex datasets
- Proficient in Python or R
- Experience in working with Spark
- Robust knowledge and experience with statistical methods
- Source code management skills using tools like Git
- Preferred degree in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Math, Information Technology or other quantitative fields (Or in pursuit of the same)
- Proven previous job stability, including maintaining long-term work relationships with former employers.
- Knowledge of SQL
- Knowledge/Experience with Shiny
- Experience with Cloudera Data Science Workbench
- Experience with Hadoop and NoSQL related technologies such as Map Reduce, Spark, Hive, Pig, HBase, mongoDB, Cassandra, etc.
- Knowledge of NLP/Text mining techniques and related open source tools