NLP (Natural Language Processing) Data Scientists – VP/Assoc Level
Location: United Kingdom (London, City of) Type: Permanent
NLP (Natural Language Processing) Data Scientists – VP/Assoc Level London based
This role is in the Equity and cross-asset quantitative strategy team within a top Investment Bank’s Equity Research department. It is a client-facing role, with both internal (primarily drawn from the equity and portfolio sales and trading teams) and external (mostly institutional and hedge fund accounts) clients, working on projects which include but are not limited to, alpha generation through stock selection, factor modeling, portfolio construction, risk modeling and analysis.
The team is looking for passionate and talented Data Scientists with a background in Information Retrieval and Natural Language Processing (NLP). Outstanding analytical and problem solving skills are essential, with a passion for finding solutions to real world, applied problems (prior finance experience is not a prerequisite). This is a critical position with the potential to make immediate, significant impacts on the business.
Employing web retrieval and text mining techniques to facilitate the collection of publically-available unstructured data.
Performing natural language, machine learning, and statistical analysis methods, such as classification, sentiment analysis, and topic modeling.
Writing regular research reports to describe novel ways on how unstructured data and machine learning approaches may enhance company and macroeconomic insights.
Working collaboratively with a team of data scientists to identify business problems, provide data-driven solutions and provide production-level products.
Articulate ideas to clients via written and oral communications.
Skills & Qualifications:
An MSc or PhD in Information Retrieval/Natural Language Processing with a solid background in statistical learning techniques associated with topic modelling and the design of recommendation systems.
Demonstrable experience with Semantic Web, Resource Description Framework (RDF)/ Web Ontology Language (OWL) / SPARQL, Linked Data, and/or Taxonomies/Ontologies.
Experience developing statistical and predictive models using software such as Apache Spark MLlib, Python, and/or R.
Experience with cloud and big data technologies, particularly Elasticsearch, Hadoop, and Amazon Web services (AWS).
Strong programming skills in at least one object oriented programming language (Java, Scala, C++, Python).
A track record of publications in the field of Data Science is highly desirable.
Excellent oral and written communication skills, including the ability to present complex technical information to a generalist audience.