DATA SCIENTIST – FINANCIAL DATA

  • Jornada Completa
  • LinkedIn
  • Madrid

Somosierra Tech

Job Description:

Bictop Inc. has an exciting opening for a Data Scientist specializing in obtaining, cleaning, structuring, and analyzing financial structured and unstructured datasets.

The candidate will be collaborating with a team of finance experts and machine learning engineers. The candidate will also be working on a broad range of research activities related to the development and implementation of these technologies.

Responsibilities:

  • Maintain data assets.
  • Design and implement efficient data preprocessing workflows for harvesting and processing structured and unstructured data (with a special focus on time series and text) in a production environment.
  • Design and develop data visualizations.
  • Collaborate with other data scientists and machine learning engineers to integrate and expand on existing pipelines and models.
  • Other engineering work as needed.

Required qualifications:

  • Fluent English (bilingual desired)
  • MS in Electrical Engineering, Computer Science, Data Science or a closely related STEM discipline, such as statistics or applied mathematics plus 3 years of relevant industry experience.
  • Candidates should have successful, proven, and demonstrable experience in time series analysis and text processing.
  • Hands-on experience with:
  • Data retrieval and web scrapping
  • Data mining, analysis, modeling, engineering, and visualization.
  • Feature engineering.
  • Data visualization.
  • Proficiency in Python.
  • Relevant experience with web scrapping and text processing libraries such as nltk, spacy, lxml, beautiful soup, and scrapy.
  • Experience with application development practices and version control systems.
  • Reviewable code samples or community participation.
  • Strong communication skills needed to present research plans, progress, and results to internal clients and decision-makers.
  • Ability to work in an interdisciplinary and multicultural teaming environment.
  • Ability to be self-directed and lead research projects.

Preferred qualifications

  • PhD or Master’s dissertation in Data Science with publication track record.
  • Familiarity with the development of ML models for time series analysis.
  • Familiarity with NLP and reinforcement learning algorithms.
  • Familiarity with alternative data science tools (Keras, Sklearn, Spark, D3, etc.).
  • Expertise in the financial domain will be a plus.
  • Familiarly with relational databases (SQL, etc.)
  • Familiarity with Linux.

Por favor, para apuntarte a este trabajo visita www.linkedin.com.