• Quantitative Researcher

    Location US-MA-Boston
    Date posted 4 days ago(5/16/2018 12:11 PM)
    Category
    Quantitative analysts
    Position type
    Full-Time
  • OVERVIEW:

    ITG is looking for an analytical, driven Quantitative Researcher to join our Financial Engineering team.

     

    Here at ITG, technology is our middle name. Literally. With nearly half of our staff working in technology roles, our technologists empower our business to provide best-in-class service to our clients around the world. From conceptualizing ideas to bringing them to market, ITG engineers work alongside our business units to build technology for institutional traders that enables them to improve returns for investors.

    WE'LL TRUST YOU TO:

    • Work closely with ITG’s entire quantitative research group to conduct formal quantitative analyses from the research question formulation to presentation of outcomes, typically including written summaries and/or business recommendations
    • Maintain and support of existing models and products
    • Apply principles of modular software development for scientific computing
    • Assist with in-depth development of models and processes
    • Effectively document use cases and requirements
    • Apply statistical, mathematical, and market microstructure theory to conduct investment and trading related research, including data collection, statistical modeling and interpretation, and implementation
    • Formally create models of risk, return, and trading cost profiles for equities and other asset classes
    • Leverage information design concepts and principles to create compelling and effective charts, tables, presentations and other visuals that convey analytical results clearly and effectively
    • Assist with project-specific guidance for others in performing analyses
    • Identify issues and areas in need of statistical analysis and/or enhancements of computational algorithms

    WHAT YOU BRING WITH YOU:

    • PhD or Master’s Degree in a quantitative field (e.g. applied mathematics, physics, computer science, applied statistics, or economics) with 0-4 years’ work experience in finance of related industry.
    • Knowledge of probability theory, statistics, and optimization methods
    • Experience with C++, Linux Shells, and Python (numpy, scipy) is required
    • Knowledge of data analysis using applied statistical methods and machine learning techniques (applied knowledge in machine learning software such as TensorFlow and Torch will be preferred)
    • Know-how in modular software development for scientific computing (algorithmic implementation, running simulations) is preferred
    • Experience in utilizing optimization modeling software to solve large-scale sparse optimization problems is preferred
    • In-depth knowledge of algorithms, data structures, object-oriented analysis and design
    • Hands-on experience with SQL or other databases is strongly preferred
    • Strong desire to develop and integrate quantitative skills within the required scope of designing and implementing analytic solutions
    • Demonstrated ability to translate research into usable, value-added tools and information
    • Strong written and verbal communication skills, including ability to effectively communicate quantitative topics and concepts
    • Ability to work independently, handle multiple tasks simultaneously and adapt quickly to changes
    • Highly self-disciplined, detail- and results-oriented

    YOU'RE JUST RIGHT FOR ITG IF YOU WANT:

    • Exposure to different technologies, such as Linux, optimization modeling, machine learning, and MS SQL
    • A smaller team environment with 10 fellow researchers
    • Direct exposure to the decision makers and senior leaders on the business side
    • A company that’s investing a sizable amount in its technology department
    • Teams that are passionate about continually learning, improving and raising the bar
    • A community that values hard work as well as work-life balance
    • A company that is committed to giving back to surrounding communities, from LA to Hong Kong and Sydney and the 11 locations in between

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