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For Companies At a Glance
- Tasks: Join us to automate data acquisition and enhance financial products using cutting-edge technology.
- Company: FactSet is a leading financial data provider focused on innovation and digital transformation.
- Benefits: Enjoy a collaborative environment, opportunities for growth, and the chance to work with advanced technologies.
- Why this job: Be part of a mission-driven team that leverages big data and machine learning to make an impact.
- Qualifications: BS or MS in Computer Science or Mathematics; 3+ years in software engineering or data science required.
- Other info: Experience with cloud environments and machine learning frameworks is a plus!
The predicted salary is between 43200 - 72000 £ per year.
At FactSet, we’re working to be the best financial data provider. We need highly motivated, talented individuals empowered to find answers through creative technology to get there.
As a Software Engineer in Data Solutions 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 market data, which are heterogeneous and voluminous datasets. With the right tools and problem-solving, we want to automate data collection at scale and infer information. The end goals are company classification, tag extraction, relationship mapping, and company valuation. There is huge potential for machine learning, analytics, and NLP.
Your responsibilities:
- Build and scale an automatic data pipeline
- Ingest and analyze various data sources to drive innovation in content creation.
- Automate the acquisition, relevance scoring, and storage of incoming sources.
- Develop processes for data mining, data concordance, and data production.
- Explore and evaluate new data technologies to build a scalable, cloud-oriented data platform.
- Optimize data retrieval and develop dashboards and other visualizations for financial experts.
- Participate in different projects as a data scientist and data engineer
- 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.
- 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, and technology.
Who are you?
- You have BS or MS in Computer Science or Mathematics related field.
- You have 3+ years of experience as a Software Engineer or Data Scientist.
- You have a successful history of writing and releasing production-grade code in an enterprise environment.
- You are a team player and adept at learning new technologies and client workflows.
- You have experience working with Agile methodology.
- You have strong analytical skills.
- You can communicate about complex subjects to non-technical stakeholders.
- You are familiar with terraform, python , pandas , and NumPy .
It is great if you have:
- Experience with Neural Networks / Deep Learning.
- Experience with information extraction, parsing, and segmentation.
- Experience with machine learning frameworks (sklearn …) and ML workflow.
- Experience with NLP libraries and text preprocessing (nltk, SpaCy, language models, …).
- Experience with cloud environments: AWS, Azure.
- Experience with business intelligence tools like Tableau or PowerBI.
- Experience working with LLMs.
- Experience working with AWS Services like EC2, RDS(Postgres), SQS, Sagemaker, MLflow, S3, API gateway, ECS.
- Experience building large distributed data pipelines.
- Experience in UI frameworks like VueJS is a plus.
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Software Engineer III employer: FactSet Europe Ltd
Contact Detail:
FactSet Europe Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer III
✨Tip Number 1
Familiarize yourself with the specific technologies mentioned in the job description, such as Terraform, Python, Pandas, and NumPy. Having hands-on experience or projects showcasing these skills can set you apart during the interview process.
✨Tip Number 2
Engage with the financial data community by participating in forums or attending meetups. This will not only enhance your knowledge but also help you network with professionals who might provide insights or referrals for the position.
✨Tip Number 3
Prepare to discuss your experience with Agile methodologies and how you've successfully collaborated in team settings. Being able to articulate your teamwork and problem-solving skills will be crucial in demonstrating your fit for the role.
✨Tip Number 4
Showcase any relevant projects that involve machine learning, NLP, or cloud environments. Be ready to explain your thought process and the impact of your work, as this will highlight your ability to contribute to FactSet's mission.
We think you need these skills to ace Software Engineer III
Some tips for your application 🫡
Tailor Your Resume: Make sure your resume highlights relevant experience in software engineering and data science. Emphasize your skills in Python, machine learning, and cloud environments, as these are crucial for the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for financial data and technology. Mention specific projects or experiences that demonstrate your ability to automate data processes and work with large datasets.
Showcase Your Technical Skills: Include specific examples of your work with tools like Terraform, Pandas, and NumPy. If you have experience with AWS services or machine learning frameworks, be sure to highlight those as well.
Prepare for Technical Questions: Be ready to discuss your previous projects and the technologies you used. Prepare to explain complex concepts in a way that non-technical stakeholders can understand, as communication is key in this role.
How to prepare for a job interview at FactSet Europe Ltd
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, Terraform, and data manipulation libraries like Pandas and NumPy. Highlight specific projects where you successfully implemented these technologies, especially in a cloud environment.
✨Demonstrate Problem-Solving Abilities
Expect to face technical challenges during the interview. Be ready to explain your thought process in tackling complex problems, particularly those related to data acquisition and automation. Use examples from your past work to illustrate your approach.
✨Communicate Effectively
Since you'll be working with non-technical stakeholders, practice explaining complex concepts in simple terms. This will show your ability to bridge the gap between technical and non-technical teams, which is crucial for this role.
✨Stay Updated on Industry Trends
Demonstrate your passion for technology and data science by discussing recent advancements in machine learning, NLP, or cloud technologies. Showing that you are proactive about learning can set you apart from other candidates.
