Principal, Data Scientist

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Data Services team is a shared service team that provides key functional capabilities such as self-service reporting, self-service data analytics, risk analytics, operational reconciliation, and integration of core processes with deployed machine learning models. We are enhancing our team and looking for Data Scientists & Machine Learning Engineers to work with us as we transform our Clearance and Collateral Technology (CCT) group into a data driven organization. The Collateral & Clearance Technology group is responsible for building high-performance critical market platforms. The group designs, builds and supports the platform used for US Triparty Repo and Global Collateral Services solutions. This service has 85% of the US Triparty Repo business with $2.7trn of assets globally. This group supports the most critical client-facing services for BNY Mellon.

In this role, the individual will work closely with Product and Business teams in analyzing business processes, requirements, workflows, client experience needs, user journeys and primarily data – gleaning information and insights with the goal of helping make business decisions. The team and the role are extremely data centric and therefore requires strong SQL and intermediate programming skills to gather and analyze information and develop recommendations to address strategic business objectives that span multiple, global business and technology areas.

Job Role:

Provides technical and organizational leadership across multiple areas the organizational and functional effectiveness of data science products. Responsible for growing, promoting and deploying the effective utilization of data products in support of the strategic priorities. Develop organizational leadership in techniques and methods to support data decisioning. Develop and communicate insights leveraging the scientific method. Roles may specialize into 3 domain specialties: model science, feature science and Insight science capabilities. Accountable for developing and guiding more junior members and communicating findings, approaches and insights from data products. Responsible for guiding own work for deployment and support.Leads complex initiatives with direct strategic impact. Maintains and grows cross organizational reltionships to further the development of data science across the enterprise. Establishes relationships to obtain data and subject knowledge needed to support advanced analytics. Conducts studies to provide additional facts needed to make informed decisions with regard to organizational and functional effectiveness with data decisioning.Develops consultative partnerships with internal teams to understand their strategic objectives, key performance indicators and reporting requirements.Extracts business insights to guide direction of learning activities and drive organizational efficiencies, effectiveness and outcomes.Maintains knowledge of company's total computing environment and planned changes in order to develop meaningful data science products.Collaborates with and supports leaders and their teams from multiple areas of expertise to ensure strategies and data science products are aligned and support business and operating results.Contributes to the achievement of area objectives

As a member of the team, you will create meaningful stories focused on deep insights, and will be fluent across various technologies and tools relevant for quantitative decision-making. You will be responsible for working with vast amounts of financial data to derive insights and make predictions about our clients and the markets in which they operate. Your primary focus will be in mining and preparing data, performing statistical analysis, implementing machine learning algorithms, and productionalizing your models to integrate with our existing systems & products. In addition to working with the rest of our technology team, you will work with our business team to derive and select use-cases best suited for machine learning solutions based on client demand and market inefficiencies.

Skills:

• Senior finance professional in quantitative discipline with expertise in machine-learning.
• Proven track record of applying machine- and deep-learning frameworks to practical business challenges in capital markets.
• Excellent knowledge of capital markets, products and concepts with a focus on fixed income products, money markets, and quantitative methods.
• Fluency in Python, SQL, Git. Proficiency in deep learning frameworks like tensorflow / keras.
• Familiarity with Google Cloud ecosystem, Bloomberg ecosystem, QuantLib are a plus.
• Team player, innovator, out of the box thinker.
• Master’s degree or PhD (Computer Science, Math, Physics, Engineering)
• At least 5 years of relevant work experience
• Applied Machine Learning experience - modeling and implementation
• Thorough understanding of various statistical and machine learning algorithms
• Proficient in Python with open source libraries such as TensorFlow and data engineering pipelines such as Apache Spark 
• Excellent analytical and big-data skills
• Academic/Research background, a plus
• Previous experience at next-gen analytics or big-data fintech companies strongly preferred

Qualification:

Bachelor's degree in a related discipline or equivalent work experience required; advanced degree is beneficial10-12 years of related experience required; experience in the securities or financial services industry is a plus.

BNY Mellon is an Equal Employment Opportunity/Affirmative Action Employer. Minorities/Females/Individuals with Disabilities/Protected Veterans. Our ambition is to build the best global team – one that is representative and inclusive of the diverse talent, clients and communities we work with and serve – and to empower our team to do their best work. We support wellbeing and a balanced life, and offer a range of family-friendly, inclusive employment policies and employee forums.