Senior Developer, Data Science Analytics

Key Skills

Microsoft-Excel, Java Programming, Management, Python Programming, Framework, SQL, Agile methodologies, Git, AWS, PowerBI, Scala Programming, Data science techniques, Alteryx, Deep Learning, MATLAB Programming, Natural Language Processing (NLP), Tableau, CUDA/GPU programming, Data Analytics, R Programming, Statistics, Algorithms, Data Modelling, SPARK Programming, Parquet, Mathematics

Job Description

The New York Stock Exchange, a subsidiary of Intercontinental Exchange, Inc. (ICE) presents an opportunity for a full-time Senior developer to join a team responsible for development of data analytics workflows. The Senior Developer will have experience in all phases of software development lifecycle, from requirements gathering, to design, coding, unit testing, debugging, and supporting in production.

The candidate will be part of a newly formed highly visible team, key to NYSE’s long-term strategy to better analyze market microstructure data to understand market behavior in a more meaningful way. The ideal candidate should be knowledgeable in Trading data processing, database systems and scripting languages.

This position requires technical proficiency/problem solving as well as an eager attitude, professionalism, and solid communication skills. Strong written and oral communication is required as the applicant will frequently be interacting with the NYSE Regulation team to achieve business goals.

Responsibilities

• Analyze requirements and propose technical solutions in delivering projects within expected parameters of cost, time, and quality
• Data format conversion to make it more appropriate for analysis
• Create experimental and new frameworks to collect data as well as build tools to automate data collection
• Remove corrupted data and fixing coding errors and related problems
• Search through large sets of data for meaningful information
• Creating reports and presentations for business uses
• Use statistical tools to identify, analyze, and interpret patterns and trends in complex data sets that could be helpful for the diagnosis and prediction
• Develop and maintain databases, data systems – reorganizing data in a readable format
• Work with project managers to compile a work breakdown structure of tasks for a given deliverable and provide realistic estimates for completing the assignment
• Develop and unit test all functions created or modified according to software development best practices
• Collaborate with other Developers and QA Engineers to execute full cycle integration, functional and regression testing.
• Continuously improve the system performance and propose better solutions.
• Effectively interact with business and operations for solving design and operational challenges.
• Brainstorm identifying ML/AI/NLP innovations to apply in quantitative analysis on market microstructure and in surveillance to help in advance automation, knowledge discovery, decision-making and insights
• Implement and prototype new algorithms and write code for novel ML/AI/NLP solutions

Knowledge and Experience

• Advanced or basic degree (PhD with few years’ experience, or MS / BS with many years’ experience) in a quantitative field such as CS, EE, Information sciences, Statistics, Mathematics, Economics, Operations Research, or related, with focus on data-driven statistical analysis & modelling
• Strong, proven programming skills in Python, Java, R , MATLAB or Scala.
• Strong knowledge of SQL and Python libraries used for data science.
• Experience in Spark SQL and PARQUET
• Experience in data visualization and business analytics tools like Alteryx, Tableau and Microsoft PowerBI is a plus
• Experience in Databricks and Snowflake is a plus
• Experience in scripting languages like AWK/bash shell scripting is beneficial.
• Experience working in Agile teams comprised of 5-8 cross-skilled engineers.
• Solid understanding of version control tools (ideally Git).
• Experience in applying data-driven statistical analysis & modelling solutions to quantitative analysis to financial market data.
• Experience with writing complex programs and implementing custom algorithms in these and other environments.
• Experience beyond using open-source tools as-is, and writing custom code on top of, or in addition to, existing open source frameworks.
• Experience in data management, data analytics middleware, platforms and infrastructure, cloud and fog computing is a plus
• Additional experience with GPU programming for training deep learning models, and cloud environments such as AWS is desirable
• Excellent communication skills (oral and written) to explain complex algorithms, solutions to stakeholders across multiple disciplines, and ability to work in a diverse team
• Experience in an applied R&D environment, working in an agile and innovation-lab culture