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Data science is one of the fastest growing fields today, and the intersection of data science and nutrition promises huge potential for innovation and job opportunities in the coming years. With nutrition playing such a crucial role in human and planetary health, the application of data analytics and machine learning to solve nutrition problems could not be timelier. 

What is Nutrition Data Science?

Before looking toward the future, let’s define what exactly is meant by “nutrition data science.” Nutrition data science is the application of data analytics, algorithms, and machine learning strategies to address important questions in human nutrition and diet. Some key aspects of nutrition data science include:

  • Collecting and analyzing large datasets related to foods, diets, nutritional biomarkers, health outcomes, and more to gain insights. Common sources of data include electronic health records, dietary intake surveys, food composition databases, and biobanks.
  • Developing predictive models to forecast things like disease risk, treatment response, food preferences, and consumer behavior based on nutritional and other variables.
  • Designing personalized dietary recommendations and interventions tailored to an individual’s genetics, biomarkers, lifestyle, preferences, and health status or conditions.
  • Discovering novel relationships and patterns in nutrition data that can generate new hypotheses for research and product/service development.
  • Automating tasks like menu planning for healthcare facilities, forecasting food supply needs, and monitoring foodborne illness outbreaks using machine learning algorithms.

So, in summary, nutrition data science leverages the power of data-driven techniques to advance nutrition research and applications at both the population and individual levels. Now let’s explore where this rapidly growing field is heading.

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Explosive Growth of Nutrition Data Science Jobs by 2024

It’s no exaggeration to say that nutrition data science is poised for truly explosive growth over the next few years, with job prospects in this hybrid field expanding dramatically. Here are a few key points about the predicted growth of nutrition data science jobs by 2024:

  • The Bureau of Labor Statistics projects a 27% increase in data scientist jobs overall between 2020-2030, which is much faster than average. Nutrition-focused roles will ride this wave.
  • As of 2022, common job titles already include Nutrition Data Analyst, Nutrition Machine Learning Engineer, Dietary Informatics Scientist, and Food Systems Data Scientist. expect many new specialized titles to emerge.
  • According to Burning Glass Labor Insights, nutrition data science job postings grew 139% between 2015-2020, and this rate of growth is projected to accelerate further.
  • Large companies like Abbott Nutrition, Nestle, and Danone are all investing heavily in internal data science teams to power new digital health solutions and precision nutrition products.
  • Startups in the nutrition tech space are thriving and aggressively hiring data science talent, like Zoe, Nutrafy, Habit, and MindBody Nutrition. Venture capital investment in these firms is also booming.
  • Government agencies such as the USDA and NIH are committing increased resources to nutrition informatics initiatives and data-driven research centers, opening up positions.
  • Academic medical centers are collaborating closely with industry on applied research and standing up joint research labs, fellowships, and faculty positions in nutritional Big Data.
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With such dynamic changes unfolding across sectors, the future for innovative careers in nutrition data science looks incredibly bright. By 2024, this field will have grown exponentially in job opportunities and specialization compared to today. The next section explores some specific job roles to expect.

Key Nutrition Data Science Job Roles by 2024

As the field expands, we will see many new and increasingly specialized nutrition data science job roles emerge over the next couple of years. Here are several key job categories and example positions that could become common by 2024:

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Nutritional Epidemiologists with Data Science Skills

Nutritional big data has opened up new horizons for epidemiology. Positions like “Nutritional Big Data Epidemiologist” will analyze large datasets to discover risk factors and evaluate policies/interventions at scale.

Clinical Nutrition Informaticists

Leveraging EHR data and real-world evidence, “Clinical Nutrition Informaticists” will build predictive models and digital tools to enhance nutrition care in healthcare settings.

Food Systems Data Analysts

With a focus on sustainable and equitable food systems, roles like “Food Systems Data Analyst” will leverage datasets on supply chains, consumption, and waste to drive positive change.

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Computational Nutritionists

At the intersection of nutrition science and computing, “Computational Nutritionists” will develop algorithms and simulations to advance our mechanistic understanding of nutrition.

Nutrigenomic Data Scientists

As nutrigenomics expands, “Nutrigenomic Data Scientists” will use multi-omics data to generate nutrition recommendations tailored to an individual’s genes.

Consumer Nutrition Data Engineers

“Consumer Nutrition Data Engineers” will build the data infrastructure and ML models powering apps, trackers, and products to guide consumer choice nudges at scale.

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These still only scratch the surface – it’s certain many new and creative job roles will emerge. The opportunities for nutrition data scientists to make an impact across sectors will grow exponentially in just a few short years.

Education and Skills Required

Naturally, as the world of nutrition data science expands, the educational pathways and skill sets needed to enter this exciting field will continue evolving rapidly. Here is an overview of the types of educational backgrounds and core competencies that will help professionals succeed in nutrition data science by 2024:

Education:

  • Nutrition sciences or public health degrees paired with data science master’s programs will remain popular and valued combinations.
  • Computer science or engineering graduates adding nutrition electives and internships to their training will also find many opportunities.
  • Certifications in data analytics, machine learning, and programming languages can boost credentials for career changers.

Programming Languages:

  • Python and R will remain dominant but expect emerging roles demanding skills in Scala, Julia, and C++.
  • Proficiency in SQL, no-code/low-code tools, and database management are baseline expectations.

Statistical Skills:

  • Beyond the usual statistics curriculum, nutritional epidemiology students are gaining exposure to techniques like survival analysis, structural equation modeling, and causal inference.
  • Experience with deep learning, computer vision, and NLP becoming increasingly important for “nutrition 2.0” jobs focused on sensor/image data.

Additional Valuable Skills:

  • Nutrition/dietetics knowledge, communication skills, and ability to work cross-functionally will give applicants an edge.
  • Big data engineering, data visualization, and experience with cloud platforms further strengthen profiles for industry careers.

As funding for applied nutrition data science grows, interdisciplinary training opportunities bridging these skill sets will proliferate. Careers will demand versatility and an appetite for continued learning in this fast-moving domain.

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Exciting New Roles in Industry, Government, and Academia

The surge of interest and investment in nutrition data science ensures jobs in this field will emerge across all sectors by 2024. Beyond start-ups, here are some notable areas where exciting new roles may be found:

Food and Beverage Companies

Established firms are creating chief data officer positions to drive data-led innovations. Expect roles like “Director of Nutrition Analytics” to optimize product formulations, shelf space, and ads based on predictive modeling of purchasing habits.

Digital Health Startups

Aggressively hire interdisciplinary “Nutrition Engineering Managers” to steward computational diet design, and adherence tracking tools integrated into virtual care platforms and connected devices.

Government Agencies

As agencies prioritize open science and access to nutrition resources, roles like “Nutrition Data Platform Architect” will help standardize heterogeneous datasets and make insights more transparent and reproducible.

Research Institutes

Interdisciplinary “Nutrition Phenomics Scientists” will lead collaborative projects applying multi-omics to nutrition questions at scale using artificial intelligence techniques.

Academic Medical Centers

As precision nutrition becomes an active area of patient care, research professor roles focused on training next-gen clinicians in “Clinical Nutritional Informatics” will gain prominence.

This is truly just a glimpse – new roles for digital solutions to nutrition problems are limited only by our imagination. Intersectoral collaboration offers many promising synergies in translating discovery into impact.

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