
Data Engineer - Quantumblack, AI by McKinsey
at McKinsey & Company
Posted 6 days ago
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- Compensation
- Not specified
- City
- Tokyo
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- Not specified
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Build and maintain the technical platform for advanced analytics engagements, spanning data science and data engineering work. Design and build data pipelines for machine learning that are robust, modular, scalable, deployable, reproducible, and versioned. Create and manage data environments with information security in mind and understand client data landscapes to assess quality. You will join a global Data Engineering community, collaborating with Data Scientists, ML Engineers, and business stakeholders to translate data into actionable solutions.
Your Impact
- Help build and maintain the technical platform for advanced analytics engagements, spanning data science and data engineering work
- Design and build data pipelines for machine learning that are robust, modular, scalable, deployable, reproducible, and versioned
- Create and manage data environments and ensure information security standards are always maintained
- Understand client’s data landscape and assess data quality
- Map data fields to hypotheses and curate, wrangle, and prepare data for use in advanced analytics models
- Contribute to R&D projects and internal asset development
- Contribute to cross-functional problem-solving sessions with your team and our clients, from data owners and users to C-level executives, to address their needs and build impactful analytics solutions
Your Growth
- Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
- A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
- Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
- World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.
Your qualifications and skills
- Degree in Computer Science, Engineering, Mathematics, or equivalent experience
- Experience building data pipelines in a professional setting (for example, internship) would be considered a plus
- Ability to write clean and maintainable code in an object-oriented language, e.g., Python, Scala, Java
- Familiarity with analytics libraries (e.g. pandas, numpy, matplotlib), distributed computing frameworks (e.g. Spark, Dask), and cloud platforms (e.g. AWS, Azure, GCP)
- Exposure to software engineering concepts and best practices, inc. DevOps, DataOps and MLOps will be beneficial
- Fluent in Japanese (JLPT N1) and business level English
FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law.
FOR NON-U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites.
Job Skill Code - DADE - Data Engineer I
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