Analytics

Data Scientist II

Job ID: 95956
  • Tokyo
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Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place.

Your Impact

Only at McKinsey you will work on real-world, high-impact projects across a variety of industries. You will identify micro patterns in data that our clients can exploit to maintain their competitive advantage and watch your technical solutions transform their day-to-day business.  
You will experience the best environment to grow as a technologist and a leader. You will develop a sought-after perspective connecting technology and business value by working on real-life problems across a variety of industries and technical challenges to serve our clients on their changing needs. 
Surrounded by inspiring individuals as part of diverse multidisciplinary teams, you will develop a holistic perspective of AI by partnering with the best design, technical, and business talent in the world as your team members. 
While we advocate for using the right tech for the right task, we often leverage the following technologies: Python, PySpark, the PyData stack, SQL, Airflow, Databricks, our own open-source data pipelining framework called Kedro, Dask/RAPIDS, container technologies such as Docker and Kubernetes, cloud solutions such as AWS, GCP, and Azure, and more! 
As a Data Scientist II, you will:
  • Partner with our clients, from data owners and users to C-level executives, to understand their needs and build impactful analytics solutions.
  • Contribute to cross-functional problem-solving sessions with your team and deliver presentations to colleagues and client.
  • Translate business problems into analytical problems and develop models aimed at solving our clients and users problems and ensure they are evaluated with the relevant metrics.
  • Write highly optimized code to advance our internal Data Science Toolbox.
  • Add real-world impact to your academic expertise, as you are encouraged to write papers and present at meetings and conferences should you wish. You will take part in R&D projects; attend conferences such as NIPS and ICML as well as data science retrospectives where you will have the opportunity to share and learn from your co-workers. Work in one of the most advanced data science teams globally.

Your Growth

Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.   
In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you’ll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else. 
In return for your unwavering dedication to excellence, you will have: 
  • 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. 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, which includes medical, dental, mental health, and vision coverage for you, your spouse/partner, and children. 

Your qualifications and skills

  • Bachelor's, master's or PhD level in a discipline such as: computer science, machine learning, applied statistics, mathematics, engineering or artificial intelligence
  • 2+ years of professional experience in applying machine learning and data mining techniques to real problems with copious amounts of data
  • Programming experience (focus on machine learning): SQL and Python’s Data Science stack are a must; good knowledge of at least one big data framework (Pyspark, Hive, Hadoop) is a plus; R, SPSS, SAS (nice to have); Software Engineering is a plus
  • Ability to prototype statistical analysis and modeling algorithms and apply these algorithms for data driven solutions to problems in new domains
  • Experience deploying technology applied to business problems is a plus
  • Knowledge in applying machine learning solution to real problems with complex and/or big amounts of data.
  • Willingness to travel
  • Fluent in Japanese (JLPT N1 or equivalent) and in English

Please review the additional requirements regarding essential job functions of McKinsey colleagues.
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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.

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