Manager of Data Science - Global Banking

Key Skills

Apache Airflow, Apache Hadoop, Apache Kafka, AWS, Azure, Data Analytics, Data Engineering, Data Lake, Data science techniques, Data Warehousing, Databricks, Google Cloud Platform (GCP), IaaS, Lakehouse, NoSQL, PaaS, SaaS, Snowflake, SPARK Programming

Job Description

Manager of Data Science - Global Banking

WHO YOU'LL WORK WITH

You will be based in one of our North America locations as part of our Global Banking Team. You will work across the region, as a cloud data science and engineering solutions architect leader. You will work closely with our clients, data engineers and McKinsey consultants on interdisciplinary projects, using math, stats and machine learning to derive structure and knowledge from raw data in the global banking sector.

This hybrid client-facing/technical role will allow you to use state of the art technologies to solve highly impactful business problems, whilst also leveraging your strong communication skills to convey complex intractable ideas to non-technical audiences.

WHAT YOU'LL DO

Working in the Chief Data and Analytics Office, you will assist with mobilizing data assets in close collaboration with client service teams including direct client access. You will assist the Global Banking Practice to adapt and transform its data ecosystems in response to rapid technology innovation in digital Big Data, blockchain, robotics, cognitive learning and automation while ensuring that the assets are fully compliant with firm’s risk practices.

Key responsibilities will include designing and delivering Cloud Data Analytics solutions using Azure, GCP and Snowflake Data technologies. You will create synergies between business and technology functions and align efforts to enable measurable business outcomes. You will be working within a project management/agile delivery methodology in a leading role as part of a wider team. You will manage practice building activities including recruiting, training and mentoring. You will play an active leading role in managing pre-sales and bid activities and provide subject matter expertise in solution design, time and resource estimations and planning.

You will work with client teams to design and implement modern, scalable data solutions using a range of new and emerging technologies from the GCP / Azure / AWS Cloud Platforms. You will establish and govern an enterprise data governance implementation roadmap including strategic priorities for development of information-based capabilities. You will deal with other stakeholders and end users in the data science and engineering development lifecycle – PMs, BAs, testing etc.

QUALIFICATIONS

• Advanced graduate degree typically required (e.g., Masters, PhD preferred, etc.)

• 8+ years of relevant technical experience in data & analytics functions. Bank/financial institution experience preferred but not a pre-requisite

• Hands-on experience architecting and delivering solutions using the Azure Data Analytics platform

• Domain experience - deep knowledge and understanding of analytical tools, technology platforms, products and its use in banking & securities sector

• Experienced working with cross functional teams, Data Scientists/Analysts and Business Managers in building Data Science and Data Engineering practice from the ground up

• Experience working with Snowflake, Databricks Lakehouse, Apache Spark, Hadoop, NoSQL, Kafka, Airflow

• Experienced in choosing SAAS, PAAS, IAAS technologies as per solution requirements

• Lead large sales pursuits with focus on data lake, data lakehouse and data warehouse solutions

• Visionary - deflect potential problems and develop innovative, via ability to communicate complex ideas effectively
• Collaborative - willingness to serve as a “bridge builder” and facilitator to traverse divisional silos