Data Scientist 1946 views

AB is a leading global investment-management and research firm with more than $500 billion in assets under management and a presence in 22 countries, with more than 3,400 employees worldwide. They serve clients ranging from institutions to individuals and private clients, and they offer independent research, portfolio strategy and brokerage-related services tailored to their clients’ unique needs. With forward-looking perspective and expertise in equities, fixed-income, alternatives and multi-asset strategies, more than 500 investment professionals collaborate to share ideas and make connections across disciplines, geographies, asset classes and sectors. These collective insights drive innovation and better solutions, helping them keep their clients AHEAD OF TOMORROW®.

AllianceBernstein is an equal opportunity employer. They do not discriminate based race, color, creed, national origin, sex, age, disability, marital status, sexual orientation or citizenship status.

Responsibilities

They are looking for a talented Data Scientist to join their Data Science team . This team is responsible for building and leveraging big data capabilities across the firm. Projects encompass all aspects of our organization, spanning research, portfolio management, trading, risk management, operations, sales and marketing. The Data Scientist will work with the stake-holders at AB to surface challenges and opportunities with big data and to lead the organization to develop solutions around algorithms, tools and infrastructure that can significantly impact their business. Initiatives include harnessing big data to improve investment outcomes and to improve sales productivity and client interactions.

Specific Responsibilities May Include

The Data Scientist is responsible for executing on AB’s projects involving large datasets and advanced statistical techniques including machine learning. In this role, (s)he will conduct research and create proto-types to address business challenges in research, investment management, sales and marketing, and operations. The individual will help develop AB’s capabilities in data science and leverage those learnings across the organization. (S)he will also help design and create an infrastructure that’s scalable and robust across the different business units. Ultimately, the Data Scientist will help the firm harness big data and advanced analytics to make better and faster decisions.

• Conduct research to extract insights from “alternative” datasets
• Utilize advanced analytical techniques including machine learning to create models to improve investment outcomes and to enhance client interactions
• Partner with data engineers and technologists to harness modern technology and techniques to create a leading-edge infrastructure for the organization
• Create tools, dashboards and open-source code to facilitate adoption of research insights, models and recommendations from Data Science team
• Collaborate with investment and client-facing teams to develop solutions to address research and business challenges
• Leverage insights across the firm by training colleagues and sharing code
• Present research findings at leading finance and data science conferences

Qualifications

The ideal candidate should have experience in finance, data science, quantitative research or business intelligence .

• Bachelors or Master’s degree in Mathematics, Finance, Computer Science, Engineering or related fields.
• 5+ years of experience working with large structured and unstructured datasets and be well-versed in big data technologies.
• Strong statistical, mathematical background.
• Proficiency in analysis (R, Matlab packages), programming languages (R, Python), and statistical modeling.

Their employees typically have track records of outstanding professional performance or academic achievement, along with excellent analytical and financial skills, as well as strong verbal communication skills. Candidates should have a strong ability to work in a collaborative environment and to present results to both expert and non-expert audiences.