
Data Science
2 weeks ago
Alpha Data Services – Data Science – Assistant Vice President
Alpha Data Services seeks team player with strong experience and interest in building Data Insight and Analytics as part of the growth in demand within Alpha Data services and our clients.
State Street is making a multi-year strategic investment in Alpha Data Services, we need a strong data science practitioner to work with internally and with clients and prospects on new Data Insight and Analytics capabilities to support our ongoing product development and execution and refinement of our multi-year strategy.
As a data scientist, you will drive real-world impact by applying innovative data-driven technology to our ever-growing dataset. You will be responsible for the end-to-end data science project lifecycle, starting from problem scoping to machine learning systems deployment and maintenance.
The ideal candidate possesses a data science background within asset management and a passion for providing insight and clear information to others so they can make better decisions. Good at 'telling stories with data'. Driven by a desire to make a difference by helping others, not least by understanding their needs and interests.
This role will report to the ADS practice lead and is hands on in terms of coding and building our analytics and insights as well as building out a small team as capabilities and demand matures.
Responsibilities
- In collaboration with the Alpha Data Service Product Domain leads , build and execute the data insights and analytics across Alphas client data sets to improve the velocity and insight of testing, build more data driven decision making and innovate towards new product capabilities.
- Assist in leveraging our technology platforms to drive data driven decisions across our service strategy and have oversight of the execution of the development roadmap.
- Work with large datasets on data extraction, cleaning, exploration, analysis, and presentation.
- Formulate data science solutions to business problems by collaborating with business and product teams and lead data scientist in region.
- Design and implement algorithms to solve a wide array of challenging problems with analytics and statistical approaches built on high-volume, high-dimensional datasets.
- Deploy, test, validate, and maintain machine learning models in production by collaborating with data engineers and machine learning engineers.
- Perform extract, transform, load operations from data sources for modelling purposes.
- Use natural language processing for to improve Chatbot when accessing and returning data sets.
- Support Implementations with insight int o the completeness and time series data sets as clients migrate.
- Create insight and learning into ongoing service delivery to improve and automate data sets and corrections into multiple tools and platforms.
Skills
- The ability to approach a problem analytically
- Strong maths and statistics
- Key influencing and collaboration skills including the ability to effectively present information and respond to questions from senior leaders at State Street, clients and prospects.
- Attention to detail and the ability to identify trends and patterns
- Able to create clear and effective visual displays of data
- Creative thinking, practical problem-solving
- Experience across the full data science project lifecycle, including:
- Engaging with stakeholders
- Data wrangling
- Modelling
- Delivering Insights (reporting)
- Strong coder, with fluency in Strong proficiency in Python, R & SQL.
- Confident ability to tell stories with data, and deliver data-driven insights to a wide range of audiences.
- Leadership and/or coaching skills
Education & Preferred Qualifications
- Minimum of 10 years of Data Science experience within an Asset Manager in an Analytics / Data Science role.
- Relevant degree subject (e.g. Computer Science, Statistics, Operational Research) and demonstrable relevant experience.
- Hands-on experience with data analytics and classical machine learning tools.
- Ability to tell stories with data, and deliver data-driven insights to a wide range of audiences.
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