Data Science Specialist - Geospatial & Agriculture Analytics

Key Skills

Java Programming, Analytical and Problem solving, Python Programming, SQL, Data science techniques, R Programming, Science, Animal agriculture optimization

Job Description

You’ll work with McKinsey’s agricultural analytics team (ACRE) in Denver, CO. ACRE is an agile team within the firm whose goal is to use the latest analytical methods, incubate new technologies and drive innovative ways to develop new opportunities for the firm to make significant and lasting client impact – redefining what it means to provide the best of the firm to our clients.

Our Agriculture Practice advises agribusiness, consumer food, government, and investor clients on strategic, marketing & sales, and operations issues, helping support industry-shaping decisions that impact the future of global food production.

Within this group, ACRE is a team of ~45 expert consultants, data scientists, and engineers focused on bringing cutting-edge analytics to our agribusiness clients. We apply real-time data and advanced analytics – generally predictive or geospatial in nature – to solve the biggest problems currently facing global agricultural markets, driving insights at the micro and macro levels.

What You'll Do

You will leverage industry knowledge and analytical expertise to provide insights both to clients as part of client service teams and within the ACRE team by strengthening the core products and algorithms we build for clients.

In this role you will split your time delivering impact at clients (either remotely or on site, when in-person travel resumes) and building up ACRE’s core analytical offerings in our Denver office (once in-person office attendance resumes).

As a member of client service teams, you will leverage your creativity and problem-solving skills to tackle clients’ most pressing issues using an analytical lens, meeting client needs and communicating your work to executive audiences. Issues to solve could include determining the suitability (now and in the future given impacts of climate change) of growing different types of crops across different geographies, using local agronomic data and satellite imagery to determine market potential for input products, or optimizing farm operations using yield forecasting. Your work will almost always include heavy geospatial components, although may also have predictive analytics components.

When working internally with the ACRE team, you will build innovative algorithms and products (what we call “IP development”) to best meet our most common client needs. You will use global data such as geospatial, biological, economic and climatological data to develop proprietary solutions. You will work with our engineers to design new interfaces to deliver faster, more impactful insights to our clients.

Along the way, you will receive best-in-class training in structuring business problems and serving as a client adviser and have opportunities to work closely with and learn from our senior agriculture practitioners and industry players that are shaping the future of food production. You will get access to unparalleled career acceleration, with a huge amount of ownership and responsibility from the get-go in a collaborative, diverse, non-hierarchical environment. You will get the opportunity to travel to client sites, locally and around the world (once travel resumes). Lastly, you will be able to provide direct and measurable impact to some of the largest agribusiness players around the globe.

We encourage you to submit a cover letter to highlight why you believe that you are a unique fit for our team and what we do! 

Qualifications

• Master’s degree in a quantitative and/or agriculture-related discipline, such as: crop science/agronomy, animal sciences, geography/GIS, computer science, ecology, mathematics/statistics, meteorology, environmental sciences, engineering, econometrics
• 1+ years of relevant professional experience preferred
• Strong analytical and problem-solving skills, paired with the ability to develop creative and efficient solutions
• Clean, efficient coding abilities, in Python and/or R, ideally with experience parallel processing and using cloud computing resources
• Strong multitasking and parallel development abilities
• Strong interpersonal communication skills
• Creative, naturally curious, and willing to take intellectual risks
• Able to work under competing, quickly-changing priorities, manage expectations effectively and support the team under pressure
• Agronomy/crop science, animal sciences, field-level yield forecasting, meteorology preferred
• Geospatial and spatiotemporal analysis, remote sensing, image processing, feature selection preferred
• Self-management skills and ability to work as part of an Agile team preferred
• Willingness to travel up to 50% (pending return to travel)