Data Scientist II
London, GBR, United Kingdom
FactSet
FactSet provides best-in-class financial data, global market insights and analytics, trusted by industry leaders to keep you ahead in finance.About FactSet:
FactSet is a global leader in providing cutting-edge research and analytical tools to finance professionals. We offer instant access to accurate and comprehensive financial data and analytics worldwide. FactSet clients integrate hundreds of databases from industry-leading suppliers into a single, powerful information system.
About Enterprise Analytics:
The Enterprise Analytics group at FactSet focuses on internal information to support product development and internal sales teams. Our work spans a diverse array of projects and teams, reflecting our broad scope and impact. We analyze user engagement patterns to identify trends and at-risk users, and recommend product bundling strategies. Our team processes and examines internal documents to uncover opportunities, and we are at the forefront of developing tools to work with data from LLM-powered tools. We collaborate closely with our stakeholders over extended periods, helping the business make informed, impactful decisions. Throughout these processes, we leverage both traditional and state-of-the-art machine learning and data analytics techniques, ensuring we remain at the cutting edge of the industry.
Job Responsibilities:
Manage and conduct data analysis and machine learning methodologies independently. This could involve running experiments, creating models, and interpreting results.
Access data from various sources and prepare it for analysis. Handle cleaning of complex datasets by identifying, addressing, and resolving issues related to quality and integrity.
Create and manage git repositories efficiently. Write clean, efficient, and reusable code adhering to best practices. Proficiency in unit testing, code profiling and cloud computing.
Work collaboratively with the data science team and other stakeholders. Communicate effectively about complex tasks, projects and insights generated from data. Present findings in a comprehensible manner to both technical and non-technical audiences.
Technology Learning Opportunities:
FactSet is committed to invest into Career development of all the Engineers to upskill, or re-skill based on individual interests, Project priorities and offers:
Licenses for learning resources like Pluralsight
Reimbursement of Technology Certification Fees (Azure, AWS or relevant Technologies)
Paid Leave for Certification Exam preparation (In addition to Casual Leaves and Privilege Leaves)
Vibrant Technology Communities that organize Internal programs, technology symposiums, Guest lectures by internal and external experts.
Requirements:
We are seeking a results-oriented person with at least three years of experience full-time Industry work in
Understanding of machine learning techniques and data processing
Proficiency in relevant programming languages (e.g. Python)
Ability to effectively manage git repositories and experience with cloud computing platforms
Expertise in accessing, cleaning, processing, and handling complex data for analysis
Excellent problem-solving skills and ability to design and execute advanced experiments testing hypotheses
Strong communication skills for effectively presenting findings to stakeholders and closely collaborating with team members
Experience with unit testing, code profiling, and object-oriented programming
Ability to work on multiple projects simultaneously and adapt to dynamic work environments
Experience with Big Data platforms like Hadoop or Spark and knowledge of SQL is a plus.
Proficiency with statistical programming and data visualization tools is highly desirable
Continual learning attitude, with a focus on enhancing both technical and soft skills
* Salary range is an estimate based on our AI, ML, Data Science Salary Index đ°
Tags: AWS Azure Big Data Data analysis Data Analytics Data visualization Finance Git Hadoop LLMs Machine Learning OOP Python Research Spark SQL Statistics Testing
Perks/benefits: Career development
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