Analytics

C&I Analytics Analyst - Geospatial Aanalytics

Job ID: 93103
  • San Jose
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Are you driven by the opportunity to tackle complex challenges and work alongside top leaders? Do you want to be part of a team that delivers outcomes that others simply can’t? If so, you’ve come to the right place.

Who You'll Work With

You will join the Geospatial Analytics team as part of McKinsey’s Global Client Capabilities Network (CCN), which includes more than 4000 diverse professionals delivering distinctive client impact and fueled by a culture of innovation.  
The Geospatial Analytics team is part of a broader research team that covers Americas market knowledge – comprised of about 50 researchers across North, Central and South America.
You will work with Geospatial Analytics team members primarily in the Americas but occasionally in Asia, Europe, and Africa as part of client service and knowledge development. You will interact with our global analytics community and partner with integrative consultants, clients, and other colleagues to deliver high-quality analyses and a great client service experience.

Your impact within our firm

You will work with the Geospatial team to create business insights from location-based analytical problems for our clients. As part of your role, you will also support team workflow administration and knowledge coordination.You will work in a fast-paced team environment combining business thinking and spatial intelligence to solve business problems across a variety of industries and geographies.  
Your work will be project-oriented, with a mix of client, knowledge, and internal initiatives. You will work closely with geospatial experts to devise and execute spatial analyses using a wide range of spatial toolkits, including open-sourced and licensed GIS software, datasets, and proprietary assets. You will clearly communicate insights to consultants and clients using a variety of forms, including written communication, compelling static and interactive charting, and data visualization. You will perform these roles through a mix of remote and some on-site client work.
Some typical projects include: working on location strategy projects by assessing the footprint of potential acquisitions to analyze areas of overlap and optimize footprints, analyzing where to place EV charging infrastructure to reach the highest number of customers and how a retailer can expand their footprint, identifying driver of performance leveraging machine learning models. Also, working on territory design or health care footprint optimizations by analyzing catchment areas for hospitals to help clients with location planning for new care units and creating optimal territory designs for reps to visit clients. You will also perform client segmentations by creating clusters for B2b or B2C clients to maximize sales, optimize pricing, marketing spent. 
In addition to serving clients, you will also contribute to McKinsey’s knowledge base on geospatial topics. We are constantly investing in knowledge development to ensure we bring best in class approaches and resources to our clients. You will spend some portion of your time building our team’s knowledge, for example, in the form of codified expertise, standardized approaches to recurring questions, exploring new sources of data, and building tools.

Your qualifications and skills

  • Bachelor’s or master’s degree from a respected institution in a relevant quantitative field (such as Computer Science, Statistics, Economics, Mathematics, etc.)
  • Strong command of English language (both verbal and written)
  • Flexibility and willingness to travel to client locations as required
  • 1+ years of data science experience, including academic experience and internships is a plus
  • Intellectual curiosity, along with excellent problem-solving and quantitative skills
  • Knowledge of a variety of machine learning and statistical techniques (such as clustering, decision trees, artificial neural networks, regression, etc.), and their application in the real world
  • Programming experience in Python and SQL is a must. Some experience with R, Scala is preferable though not essential
  • Familiarity with geospatial analysis, spatial statistics, network analysis, and geographic visualization and experience in working with GIS tools (e.g. ArcGIS, QGIS, PostGIS) would be an added advantage
  • Familiarity with data visualization tools and platforms (e.g. Tableau, Power BI, R Shiny, Kepler) to visualize data and provide insight
  • Experience with big data: extraction, processing, filtering, and presenting large data quantities via AWS
  • Strong team-orientation and a professional attitude
  • Good presentation and communication skills, and the ability to translate complex analytical concepts to business stakeholders
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/Affirmative Action 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 Group - N/A
Job Skill Code - CIAA - Capabilities and Insights Analytics Analyst
Function -
Industry -
Post to LinkedIn - Yes
Posted to LinkedIn Date - Tue Nov 05 00:00:00 GMT 2024
LinkedIn Posting City - San Jose
LinkedIn Posting State/Province -
LinkedIn Posting Country - Costa Rica
LinkedIn Job Title - C&I Analytics Analyst - Geospatial Aanalytics
LinkedIn Function - Analyst;General Business;Research
LinkedIn Industry - E-Learning;Market Research;Research
LinkedIn Seniority Level - Entry level