Apply NowApply Later YOUR QUALIFICATIONS AND SKILLS Bachelors, Masters 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 Knowledge in applying machine learning solutions to real problems with complex and/or big amounts of data Ability to proto@type 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 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 Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment. Willingness to travel Strong language fluency skills, both verbal and written, in English, with the ability to adjust your style to suit different perspectives and seniority levels Apply NowApply Later Share This Job Equal Opportunity Employment Disclaimer McKinsey & Company is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, national origin, disability, veteran status, and other protected characteristics.

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Data Scientist II QuantumBlack, AI by McKinsey