Data Science Manager, Portfolio Analytics Group, Vice President

Key Skills

Java Programming, Python Programming, SQL, DevOps, AWS, Google Cloud Platform (GCP)

Job Description

Portfolio Analytics Group (PAG) within BlackRock Solutions delivers actionable insights to our investment and client teams by applying data and financial models through Aladdin technology to influence portfolio decisions.

Team Description:

PAG Data Science team within PAG has a mission to deliver solutions that enable stakeholders to derive greater value, identify opportunities across PAG solutions for scale and reuse and advance team’s analytical maturity and career progression.

The team is located in BlackRock’s Atlanta innovation Hub (iHub).

Role Description:

The team seeks a talented Data Science manager who will use their analytical and technical skills to generate actionable insights for portfolio decisions made by our investment, risk and client professionals. This position requires demonstrated experience leveraging statistical, machine learning and modern scripting techniques and working with different data architectures to derive insights and build data and analytic solutions. Equally important, this position requires helping manage a team of 2-3 analysts/associates, developing their careers and ensuring execution of multiple projects for a suite of stakeholders. Candidates will be expected to build strong knowledge of financial markets and achieve a deep understanding of investment processes spanning different asset classes. As a technologist, you will contribute to the deployment of our Aladdin Studio toolkit to internal and external clients via research, reporting, and idea-generation projects.

Responsibilities:

• Help manage a team with the skills, capabilities, and inspiration necessary to successfully drive and sustain a data science focused culture
• Comfortable working as an individual contributor, in addition to a managerial role, as and when needed
• Collaborate with stakeholders and partners throughout the organization and leaders within PAG to understand business needs
• Lead and execute multiple data science projects (automation, ML, interactive tools) with the urgency appropriated for the business objectives across the spectrum of data science techniques to datasets large and small
• Advance existing initiatives and open opportunities to pursue new and previously unexplored research topics across a wide variety of domains and the broader data sciences and analytic community in BlackRock and Atlanta
• Willingness to learn and educate others on new tools and techniques as needed
• Leverage wealth of available data stored in variety of internal and external data stores to deliver actionable insight to drive the decision-making process
• Visualize and explore data sets to enable the ideation and generation of new, predictive feature
• Focus on automation and utilizing technology to provide repeatable solutions
• Master the Aladdin Studio Toolkit and share this knowledge with the whole of PAG

Qualifications:

• 6-10 years of experience in a highly analytical role in a technology or financial services setting
• Strong Python coding skills required
• Knowledge and experience applying statistical and data science methods required (supervised learning, unsupervised learning, time series forecasting, deep learning and natural language processing)
• Experience working with big data and cloud compute services (Azure, GCP) preferred
• Knowledge of Azure DevOps functionality like source code management (SCM) preferred
• Broad and proficient knowledge of modern techniques in scripting, experience querying databases in SQL and using distributed data/computing technologies
• Experience in financial modeling, analytics, and investment systems preferred
• Proven experience managing a team, established success delivering to a diverse client base
• Relentless desire for understanding how processes work.
• Creativity/innovation in solving unconventional problems, entrepreneurial drive to learn new skills and technologies.
• Advanced degree in Data Science, Computer Science, Operations Research or similar field is preferred