Data Science Specialist - Agriculture Marketing and Sales Analytics

Key Skills

Java Programming, Python Programming, SQL, Azure, AWS, Machine learning techniques, Data science techniques, Prophet, Jupyter Notebook, Keras software library, PyTorch, TensorFlow, Google Cloud Platform (GCP), Scikit-learn, Linux Operating system, Github, Databricks, RStudio, PyCharm, LightGBM, MS Visual Studio

Job Description

As a member of the Agriculture Growth Analytics team (or Ag Growth Analytics team), you’ll work with McKinsey’s agricultural analytics team (ACRE-Agriculture Commodities Research Engine), McKinsey’s Agriculture practice, and client service teams that support clients across sectors and geographies. This role is based in Denver, Colorado. 

Ag Growth Analytics harnesses large data sets with numerous features, advanced analytics, and machine learning to drive commercial growth at agricultural players across the agriculture value chain. 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.

ACRE is a team of ~50 expert consultants, data scientists, and engineers focused on bringing cutting-edge analytics to agriculture & related clients. 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

As a Data Scientist on the Next Generation Commercial Growth sub-team of ACRE Ag Growth Analytics, you will apply and grow ACRE’s data science capabilities and client-facing advanced analytics assets across a broad range of commercial and marketing and sales topics as applied to agriculture. You will leverage your advanced analytics experience to drive data science work within ACRE and on the ground with our clients.

As a member of client service teams, you will serve as a thought partner and practitioner, aligning methodological approaches with client and asset development objectives, and writing generalizable and reusable code that can be tailored to specific client needs. You will act as an analytics translator with stakeholders while also advising clients throughout the stages of model development.

Issues to solve include a range of commercial growth topics – from how to acquire new customers, prevent customers from leaving, or provide advanced cross-sell product recommendations to customers. Your work will include heavy data processing, advanced analytics, and machine learning to develop predictive and prescriptive recommendations to end users. Your work will be grounded in both data science knowledge, and domain/content knowledge, as you adapt and create techniques that leverage the rich context of agriculture data, often containing complex dynamics involving seasonality and agronomy. 

When working internally, you will build innovative algorithms and products (what we call “IP development”) to best meet our most common client needs. You will also work with our engineers to design new interfaces to deliver faster, more impactful insights to our clients. You will collaborate with other team members and apply technical best practices, methodologies, leadership, and communication/technical translation.

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.

Qualifications

• Master’s or above degree in a quantitative discipline such as computer science (especially machine learning), applied mathematics, statistics, behavioral economics, quantitative finance, or industrial engineering
• Strong experience developing predictive marketing and sales models (regardless of industry)
• 2+ years of hands-on modeling experience in business environment
• Expertise in deploying production-ready Python code, including developing modular code to be run in a production environment (e.g., remote server, virtual machine, cluster), writing readable and structured code that can be understood and extended by others utilizing data structures effectively, writing unit and integration tests, showing familiarity with design patterns, and following software development best practices
• Advanced knowledge of statistical and data mining techniques (regression, decision trees, clustering, neural networks, etc.). Strong machine learning background, with experience implementing machine-learning models and dealing with large data sets, especially in models that have a strong time component 
• Experience working in multidisciplinary teams on fullstack development (e.g., software engineers, data engineers, front-end developers, UI/UX)
• Strong understanding of tech stack, including experience working in a cloud environment (AWS, GCP, Azure, Databricks), familiarity with Linux terminal, experience using common machine learning libraries and frameworks (e.g., LightGBM, Prophet, Pytorch, Tensorflow, Keras, ScikitLearn), 
• Experience collaborating in git version control and in GitHub
• Experience working with production level IDEs (e.g., Visual Studio, PyCharm), interactive IDEs (e.g., spyder, Jupyter), preferred
• Intellectual curiosity with excellent problem solving and quantitative skills including the ability to disaggregate issues, identify root causes and recommend solutions, with strong multitasking and parallel development abilities
• Distinctive communications skills; ability to communicate analytical and technical content to senior stakeholders in a simple way
• Willingness to travel up to 50% (pending return to travel)
• Willingness to relocate to Denver, CO