At FactSet, we're working to be the best financial data provider on earth. To get there, we need highly motivated, talented individuals who are empowered to find answers through creative technology.
As a Senior Data Science Engineer in Content Engineering, you will be part of our Digital Transformation, a mission to automate our data acquisition, quality assurance, content creation and analytics in a scalable cloud environment. With the guidance of financial experts, you will leverage these large data sets to improve the quality and extend the scope of FactSet's existing and next generation products.
You will be working on private markets data; these are heterogeneous and voluminous datasets. With the right tools and problem solving, we want to automate data collection at scale and infer information. There is huge potential for machine learning, analytics and NLP.
What you will be doing?
- Bring your experience within the team
- Participate to different projects as data scientist / ML engineer
- Help conceive solutions with ML and NLP
- Make sure to align with business needs
- Deliver clean, well-tested code that’s reliable, maintainable, and scalable
- Build predictive models and communicate results with stakeholders
- Deploy working solutions
- Develop dashboards and other visualizations for financial experts.
- Ingest and analyse structured and unstructured data
- Develop processes for data collection, quality assessment, and quality control.
- Keep up to date / share your passions
- Stay up to date with state-of-the-art approaches and technological advancement
- Share your passion for science, ML, technology, …
- Collaborate with other ML teams
Who you are?
- You have BS or MS in Computer Science or Mathematics related field .
- You have 5+ years of working experience as ML Engineer or Data Scientist.
- You have senior experience with ML and NLP
- You have a successful history of writing production grade code and releasing in an enterprise environment.
- You are a team player
- You have strong analytical skills
- You are fluent in English ; you can communicate about complex subjects to non-technical stakeholders
- You master: python, pandas and numpy
- You are expert with machine learning frameworks ( sklearn …) and ML workflow
- You are familiar with NLP libraries and text preprocessing (nltk, SpaCy, Stanza, Flair, Polyglot, gensim, language models, ... )
It is great if you have:
- Experience with Neural Networks / Deep Learning.
- Experience with information extraction, parsing and segmentation,
- Knowledge on ontologies, taxonomy resolution and disambiguation.
- Experience in Unsupervised Learning techniques Density Estimation, Clustering and Topic Modelling.
- Experience with cloud environments: AWS, Azure, GCP, …
- Experience in data visualization tools like DataViz, Graphana, Apache Superset…
- Experience with business intelligence tools like Tableau or PowerBI.
- Experience with modern data platforms such as Spark, Hadoop or other map/reduce big data systems and services.