Data Scientist AVP - Research

Barclays•New York, NY

1d•$125,000 - $175,000•Onsite

About The Position

Join us as a Data Scientist AVP - Research within our Investment Bank Research Central function. The Central Research team delivers actionable insights to clients, partnering with them to support informed investment decisions. As a Data Scientist, you will help integrate data science into the investment process across a range of financial asset classes through the use of Python programming and machine learning models. Working alongside Research Analysts, you will produce detailed data-led research that can be published and used in client discussions. You will also contribute to other mandates within the Data Science team, including the publication of standalone data-led research focused on niche markets and partnering with business stakeholders to translate data insights into actionable strategies.

Requirements

Coding in Python, PySpark, R, SQL or other scripting languages
Understanding of Machine learning and Math statistical modelling
Considerable academic background in a quantitative/empirical field (math, statistics, economics, computer science, physics, chemistry, etc)
FINRA regulated role

Nice To Haves

Demonstrated ability to tell stories that extract the key implications and underlying intuitions from highly detailed models
Snowflake/ Databricks and/or Tableau/Power BI experience
Understanding of fundamentals or strategy approaches to research

Responsibilities

Analysis of market, sector, corporate and/or economic data to help develop investment theses for your coverage universe to produce best in class Research.
Research may range from individual company or sector notes, through to long dated thematic reports.
Presentation of Research views to Barclays Clients; this can be through direct, face to face and virtual interactions, Research hosted events and written communications.
Engagement with Markets, Client Strategy and other stakeholders, to raise awareness of your Research both to Clients and internally.
Prioritise interaction with the most relevant and valuable Clients for your Research.
Provision of insights and Research views to internal Clients to help them navigate financial markets and risks.
Collaboration with the Supervisory Analyst, Compliance and other stakeholders to ensure Research is produced and delivered to Clients and internal stakeholders in a compliant manner.
Help integrate data science into the investment process across a range of financial asset classes through the use of Python programming and machine learning models.
Produce detailed data-led research that can be published and used in client discussions.
Contribute to other mandates within the Data Science team, including the publication of standalone data-led research focused on niche markets.
Partner with business stakeholders to translate data insights into actionable strategies.
Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function.
Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes.
Lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments.
Identify new directions for assignments and/or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
Take ownership for managing risk and strengthening controls in relation to the work done.
Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc) to solve problems creatively and effectively.
Communicate complex information.
Influence or convince stakeholders to achieve outcomes.