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Intern - Data Scientist - Agriculture Commodity Research Engine (ACRE)

Title
Data Scientist Intern, ACRE

WHO YOU’LL WORK WITH
You’ll work with McKinsey’s agricultural analytics team (ACRE) in Denver, CO.

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 ~35 expert consultants, data scientists, and engineers focused on bringing cutting-edge analytics to our agribusiness clients. We develop software products for continuous client use as well as deploy our advanced analytics capabilities within standard client engagements. 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.

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.

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. You can expect to spend about half of your internship delivering impact at clients (either remotely or on site) and half your internship building up ACRE’s core client offering in our Denver office.

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, customizing ACRE’s offering to best meet client needs and communicating your work to executive audiences at the client. Issues to solve could include predicting future market price trends, 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.

When working internally with the ACRE team, you will improve our offering by building 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 using data science skills in timeseries forecasting, dimensionality reduction and feature selection, and machine learning. You will work with our engineers to and 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 potentially get the opportunity to travel to client sites. Lastly, you will be able to provide direct and measurable impact to some of the largest agribusiness players around the globe.

This is a full time opportunity lasting approximately 10 weeks. Ideal start date will be anytime after June, 2020 and is negotiable.


Qualifications:
■     Junior working towards undergraduate degree or more senior (working towards Masters/PhD preferred) in a quantitative and/or agriculture-related discipline, such as: data science, economics (especially econometrics), mathematics (especially statistics), atmospheric science, computer science, geography, crop science/agronomy, and the environmental sciences
■     Strong analytical skills (geospatial and/or predictive in nature)
■     Clean, efficient coding abilities; will consider all languages but rest of team uses R and/or Python so those are preferred
■     Self-management skills and ability to work as part of an Agile team
■     Strong multitasking and parallel development abilities
■     Strong analytical and problem-solving skills paired with the ability to develop creative and efficient solutions
■     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
■     Willingness to travel up to 50% (will likely travel 20-40%)
■     Time series or econometrics modeling and feature selection with y << X (e.g. regularization algorithms like LASSO) a huge plus
■     Experience with trading or price-discovery, field-level yield forecasting, GIS mapping, Earth observation, agronomy/crop science, and/or weather/climate analytics a huge plus
■     Experience creating and implementing machine-learning models and dealing with huge data sets (e.g., through parallel processing and using cloud computing resources) a plus