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.
- 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.
- 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.
- 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.
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