Senior Data Scientist - QuantumBlack, AI by McKinsey - Johannesburg
McKinsey
You will join our QuantumBlack, AI by McKinsey Africa team based in Johannesburg. Our QuantumBlack, AI by McKinsey teams bring the latest analytical techniques plus a deep understanding of industry dynamics and corporate functions to help clients create the most value from data in order to unlock the strategic CEO agenda. Your role will entail extensive interactions with our global analytics community; partnering with generalist consultants, clients, and other colleagues. You will be involved in specific engagements involving the building of new and bespoke advanced analytics solutions for clients. You'll dive into complex data sets across a rich variety of industries, functions and geographies while remaining a core member of the strategy team, injecting your analytics thinking on meaningful client projects. You will shape solutions tailored to the needs of our clients, maximizing programming languages (e.g., R, Python), tech platforms, and disruptive analytics methodologies (e.g., Casual Inference, Bayesian Optimization, Geospatial Analytics, Natural Language Processing) as part of our tech-agnostic firm. As a senior data scientist and consultant, you will have the opportunity to get in-depth exposure to emerging methodologies and programming languages through hands-on client projects, e-learnings, certifications, live bootcamps and global analytics conferences. You'll also benefit from our established, formal leadership and consulting-toolkit trainings to support your personal and professional goals, from being a data-science manager to a firm partner to a Chief Analytics Officer. LI-MP Bachelor's degree in quantitative field like computer science, engineering, statistics, mathematics or related field required; advanced degree is a plus 3 years of hands-on mathematical modelling experience in business environment Programming (focus on machine learning) in Python (must), SPSS, SAS, Ruby, Hadoop (valued) Data treatment/Data mining SQL, AWK, Access, Spark, Excel (valued) Advanced knowledge of statistical and machine learning techniques (regression, decision trees, clustering, neural networks, etc.) Proven experience in working with large datasets and relational databases (SQL) Distinctive communications skills and ability to communicate analytical and technical content in an easy to understand way Excellent problem-solving and quantitative skills, including the ability to disaggregate issues, identify root causes and recommend solutions Proven leadership with the ability to inspire others, build strong relationships, and create true followership, result-driven achievers Strong people skills, team-orientation, and a professional attitude Experience and interest in RDBMS systems (MySQL, IBM DB2, Oracle Database, etc.), cloud (AWS, Azure, Google Cloud Platform) and big data technologies (e.g. Hadoop, Hive, Impala, Spark, NoSQL DBs) is preferable Experience in data extraction, transformation, cleaning, and validation Experience implementing advanced analytics/data science models into a production environment is a plus
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