Data Scientist II
- 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.
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.
- 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
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