Lead Data Science Engineer

Key Skills

Java Programming, Python Programming, Database, SQL, PowerBI, Apache Hadoop, Data science techniques, Alteryx, Tableau, R Programming, SPARK Programming

Job Description

Known for being a great place to work and build a career, KPMG provides audit, tax and advisory services for organizations in today’s most important industries. Our growth is driven by delivering real results for our clients. It’s also enabled by our culture, which encourages individual development, embraces an inclusive environment, rewards innovative excellence and supports our communities. With qualities like those, it’s no wonder we’re consistently ranked among the best companies to work for by Fortune Magazine, Consulting Magazine, Working Mother Magazine, Diversity Inc. and others. If you’re as passionate about your future as we are, join our team.

KPMG is currently seeking a Lead Data Science Engineer to join our Data Strategy & Operations organization.

Responsibilities:

• Work with KPMG’s Data Scientists, the candidate will create information architecture supporting hypothesis testing, model training, and model promotion activities
• Build free-flowing data integration processes supporting both discovery and production enabled advanced analytics assets
• Construct visualizations simplifying complicated advanced analytics concepts
• Organize effective alerting and monitoring capabilities of existing models ensuring their long-term accuracy and efficacy
• Manage the ongoing evolution of Data Bricks as the backbone of KPMG’s Data Science capabilities
• Orchestrate APIs integrating advanced analytics to downstream systems and receive feedback about the actions taken by users

Qualifications:

• Minimum eight years of relevant experience and strong knowledge of data analytics, data engineering, AI/ML, including following fields: machine learning, data integration, data analysis, data visualization, data, and model governance
• Bachelor's degree from an accredited college/university; Master's degree from an accredited college/university is preferred
• Proficiency in analytics tools and programming languages (R, Python, Spark, Hadoop, Alteryx, etc.), databases (SQL and no-SQL), data visualization tools (Tableau, Power BI, etc.)
• Strong understanding of the data science software development lifecycle including experience and skills enabling data scientists to perform their work; solid knowledge of cloud infrastructures and core services across storage, compute, machine learning, data integration
• Strong communication skills and ability to present complex information concisely through written & verbal communication; experience hosting interviews, brainstorms / workshops with business teams and executives on data-related topics / projects
• Natural curiosity in emerging technology trends with a focus to maintaining data science capabilities in alignment to business trends; demonstrated organizational skills with cross-functional teams and data domains including frequent alignment with information architecture