December Data Science Job Market Report (2023)

Looking at data science job listings for November - job numbers remain below historic levels. FAANG and big tech companies have rebounded with Meta and Amazon leading the charge and driving FAANG growth.

• Job Listings Stagnant – New postings in November remained depressed.
• Market Share of FAANG Jobs – Rising listings for FAANG and declining listings overall have boosted their share.
• Meta Invests in AI – Roles in Machine Learning and Research are driving Meta’s hiring spree.
• Amazon Hiring Rose - While there may be some seasonality to this, hiring at the company is elevated from 2022.

Just like the wider job market, listings are mostly in a small decline. What we’re seeing is a typical slowdown for the winter season, as companies are preparing for planning in 2024.

Over the last month, data science postings have declined by 17.7% and data analyst roles by 13.9%, but data engineering remained more stable, with a small 2.2% increase.

Year over Year declines continue to look steep (-37% in total listings), but are slightly better than in September of this year (-41%).

In September, YoY openings for Data Science were down 32.1% vs 31.3% today, down 47.9% vs 44.1% today for Data Engineers, and down 40.8% vs 37.1% today for Data Analysts. Only BI openings have worsened since September, from being down 22.9% to around 30.8% today on a YoY basis.

We’ll likely see next months numbers go up in comparison to YoY but we’ve heard of companies tightening their belts in anticipation of 2024. Remember last year we saw layoffs peak in December / January of 2023, which means that year over year numbers should look better in the new year.

Continuing the upward momentum from their low point of 0.54% in January 2023, FAANG has jumped in November to yearly high comprising of 4.46% of all job listings. This represents a 44% increase from October, and is on par with June 2022 levels.

Two factors are driving this market share up; an increase in FAANG listings and an overall decline in the total number of jobs being posted.

Listings from Meta have especially helped the rising dominance of FAANG companies.

In raw listings, Meta jumped from 41 to 86 data science postings from October to November.

Within that, however, one role is driving that growth more than any other. Machine learning engineering, which includes AI and research scientist roles, rose to 51 jobs in November from 21 in October, accounting for almost all of their hiring increases.

So why is Meta making such a big investment? Artificial Intelligence.

In their Q3 earnings call, Mark Zuckerberg declared that “AI will be our biggest investment areas in 2024 — in engineering and computing resources”. While much of this is internal, he also stated that they were working through a temporary hiring backlog that was driven by last year’s restructuring: in other words, the window to join the team might be brief.

Here is one such role that they are currently hiring for!

Research Engineer, Language - Generative AI

Salary: $143,000/year to $204,000/year + bonus + equity + benefits

• Design methods, tools, and infrastructure to push forward the state of the art in large language models.
• Define research goals informed by practical engineering concerns.
• Contribute to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results.
• Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
• Work with a large and globally distributed team.
• Contribute to publications and open-sourcing efforts.

Amazon also saw a rise in their data science listings, increasing their hiring by 18% from October to November, to a total of 198 data roles from 168.

Their growth has mostly been driven by hiring for data scientists (63 from 43) and data analysts (86 from 70), with small declines in other roles, like data engineering (38 from 45).

It is unclear if this rise in data science hiring is being partly driven by the holiday season, although Amazon did say they would be bringing on “250,000 full-time, part-time, and seasonal employees in the U.S.” for the expected surge in purchasing. Since this period coincides with their rounds of layoffs last year, the same seasonality surge could not be observed in 2022, when November data science hiring stood at only 73 listings.

You can expect to find roles like this one currently on their Jobs Page!

Data Scientist - Kumo

• Deliver real world production systems at AWS scale.
• Work closely with the business to understand the problem space, identify the opportunities and formulate the problems.
• Use machine learning, data mining, statistical techniques, Generative AI and others to create actionable, meaningful, and scalable solutions for the business problems.
• Analyze and extract relevant information from large amounts of data and derive useful insights.
• Work with software engineering teams to deliver production systems with your ML models
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation