Have you ever mixed Nutella and soy sauce?
Apparently, running to the local grocery store, stacking up the office with those ingredients, and tasting various combos between the two, is just an ordinary workday for the data science team at Spoonshot – one of the best startups hiring data scientists at the moment. The experiment used Taste Intelligence System (and a lot of trial and error) to find products that share similar compounds with Nutella’s legendary hazelnut and cocoa aroma. In the end, Spoonshot’s taste insights revealed new cross-promotion strategies to increase penetration in under indexing markets for their client.
Sounds like fun, right?
And that’s just one example of the many exciting projects you can work on in the hottest startups.
Why Work for a Startup?
Sure, big data science consultancies have the stability and the benefits every aspiring data scientist strives for. However, you may find yourself working on predictable and often repetitive tasks with little opportunities for growth. At least for the first few years.
Startups, on the other hand, allow you to develop your skillset by trying new things and handling a variety of challenges. Responsibilities there change quite frequently. So, within less than a year you could be doing something entirely different... And a lot more interesting for you than what you were initially hired for. In other words, the sky is the limit!
That said, before you start sending out your resume to Bain and McKinsey, consider the list of best startups for data science we’ve carefully curated for you.
We based our research on insight from KDnuggets, LinkedIn, and Forbes to discover the best startups to watch in 2023. Then we picked our top 10 - the fastest growing machine learning and tech startup companies that give you both development opportunities, and a chance to work on inspiring projects.
So, read on to learn what they do, where to apply, and why you should consider working there. And don't mind the order - these startups are so unique, that every single one of them could easily be number 1 on our list.
1. Cinnamon AI
What they do: Does your employer despise paperwork? This Japanese AI startup found a solution. Cinnamon is devoted to eliminating boring and repetitive business tasks. Their cognitive document reader cinnamon.ai automates data extraction. It crawls all types of unstructured documents (invoices, financial statements, and even hand-written text). Thus, it saves millions of hours of manual input and reducing costs of enterprise operations.
Where to apply: The startup’s primary office is located in Tokyo. However, you can check for openings in any of their 2 offices in Vietnam, Taiwan, or the US.
Why work there: Cinnamon is constantly on the lookout for top-tier talent. According to Forbes, the company has successfully recruited over 50 data scientists with the goal of having 100 by the end of 2019. Talk about fast expansion! Apart from joining an award-winning team that works with top-notch clients, you’ll also have the opportunity to develop an exciting ML product with a steady increase in demand. So, we can say the future certainly seems bright for members of the Cinnamon team.
What they do: Oden Technologies has developed a ground-breaking Industrial Internet of Things (IIoT) platform. Using devices plugins and existing ERP systems integration, it helps manufacturers solve their constraints related to production processes, plant inefficiencies, output and reduction goals, and production quality. Their all-in-one software performs real-time root-cause analysis and helps clients to immediately understand the impact of changes they implement in their production. In short, Oden Technologies makes your factory super smart.
Where to apply: Based in New York, this up-and-coming startup is also hiring in London, so you can literally make a difference on 2 continents.
Why work there: As mentioned in a Harvard Business Review article, for a client’s project, Oden’s team managed to build a tablet-based system for real-time complex calculations in just 10 weeks, when the usual time to develop a product like that is between six months and a year! In addition, Oden’s co-founders Willem Sundblad and Peter Brand were featured in last year’s Forbes’ Europe 30 Under 30 in Industry list. Who wouldn’t want to be part of that super team?
What they do: Welcome to the brave new world of food science and taste intelligence! Spoonshot’s innovative AI technology helps solve the F&B industry biggest challenges by understanding and predicting people’s tastes. Their products include AI-powered Genesis system which delivers insights for product development ideas, the HungerBox platform that generates personalized menu options, and a Guest Intelligence app to track customers’ experience.
Where to apply: Bangalore or Minnesota – wherever your passion for food and ML leads you!
Why work there: As a data scientist in this food tech startup, you’ll be able to conceptualize and develop novel techniques to understand food data and improve the “foodbrain” personalization algorithm. Furthermore, you’ll have the chance to pick up knowledge in chemistry and biology by working closely with food scientists (so cool) in a highly-motivated team. There’s also a 6-month data science internship opportunity. The startup’s career page says “Calling all foodies… Spoonshot needs YOU”. No need to ask twice, Spoonshot – we’re in!
What they do: Siren is an investigative intelligence platform that uses a unified data model, a.k.a. ontology, to represent detailed relationships between entities in a domain. Simply put, it can narrow down a law enforcement search of a suspect’s car way further than color and make. For example, Siren’s capabilities allow investigators to leverage other datasets and find a specific vehicle owned by suspects in a certain age group whose mobile was in the area on a given date.
Where to apply: Siren’s HQ is located in Galway, Ireland. However, you can opt for its offices in Dublin, Cambridge, Bordeaux, Trento, and Philadelphia.
Why work there: You’ll work on a cutting-edge product in a fast-paced startup environment with tons of development opportunities. This is just the beginning for Siren, as it won Tech’s excellence award for Startup of 2018, Technology Innovation of 2018, and ITag’s Enterprise Company of the Year SME and Technology Innovation of the Year for 2019. Some of its partners include IBM, Capita and Excelerate Systems.
What they do: Sesamm’s strong innovation team turn emotions into investment wins. How so? Their application taps into more than 250,000 big data resources and analyses billions of news articles, social media, blog and forum posts to help predict financial markets movements. The startup uses NLP algorithms, ML models, and Quantitative analysis to turn big data into smart data that will ensure a competitive edge to their clients.
Where to apply: You can check out the open positions in Metz, Paris or Luxembourg. There are opportunities to apply for both senior positions or data scientist internships if you’re just getting started on your data science career path.
Why work there: Sesamm has won numerous awards, including Pass French tech – France's Hyper-Growth Startups, Early Metrics – Top 6% of Evaluated Startups, SOCIETE GÉNÉRALE – GLOBAL MARKETS INCUBATOR. Moreover, the startup has been recognized by many high-profile clients and partners. That sounds great, but what will working there actually be like? Well, as a data scientist at one of the best startups, you’ll develop Machine and Deep Learning-based algorithms, collaborate with the strategist team and be a source of proposals for financial interpretation of probabilities outputted by their models.
What they do: This data science startup delivers the most advanced R Shiny apps, data science consulting services and support with R Shiny and Python Dash technologies. Appsilon boasts an impressive portfolio with projects across numerous industries – finance, retail and e-commerce, healthcare, real estate, and even maritime transportation. For Appsilon, no time zone is out of reach – companies in the US, Europe, even Hong Kong, and Australia are no strangers to its services. Moreover, its list of partners includes “A” players like BCG, NAMU Systems, Diversey, Viacom, and more.
Where to apply: Appsilon’s offices are located in Warsaw and Gdansk. Lucky for you, speaking Polish is not an absolute must, as most of its clients are international.
Why work there: Appsilon’s founders have been working together for over 10 years, merging their experience from companies like Google, Microsoft, Bank of America and UBS into their own company. That makes it a great learning place, especially if you’re just starting your career. You’ll join an award-winning team with an enviable skill set and work on fascinating data science and artificial intelligence projects. As team members share: “One day we process satellite imagery to search for a ship, another, we analyze sales data of an international retail company.” So, make no mistake, there'll be no boredom in Appsilon town.
What they do: Addepto provides custom-made AI models and BI solutions to give companies a competitive edge, optimize their operations and increase ROI. Its scope of BI projects includes developing OLAP and Tabular cubes and implementing customer data visualization tools, such as Tableau, Power BI, and Looker. Addepto’s clients are diverse – from large enterprises to small and medium-sized companies. On top of that, it helps other startups enhance their products with ML solutions using Python and AI-powered features.
Where to apply: Europe or the US – it’s up to you to make your pick, as Addepto has offices in both Warsaw and New York.
Why work there: You’ll gain experience in creating and implementing ML and DL algorithms with the active support of experts in the field. You’ll also have the chance to put your SQL, Python, and R knowledge into practice with projects in finance, logistics, manufacturing, and marketing. Plus, Addepto will finance the courses you need to achieve your career goals. The way we see it, these are all great development opportunities.
What they do: STATWORX is a data science consultancy which quickly became a leader in the German-speaking world. Its slogan “Data Science and AI Done Right” pretty much speaks for itself. So far, this startup has successfully implemented more than 200 cross-industry Data Science and AI projects, focusing on optimizing products, services, and processes through the use of statistical and mathematical models. It also provides hackathon workshops where they teach clients how to develop the first working prototype of their data science use case with tools of their choice.
Where to apply: Sprechen Sie Deutsch? That would definitely be a plus, as STATWORX’s offices are in Frankfurt, Zurich, and Vienna.
Why work there: Working at STATWORX will present you with technical challenges and a steep learning curve while building up your data science expertise. You’ll work on exciting projects with prominent clients, such as Mercedes Benz, Volkswagen, Bayer, and Hyundai. You’ll actively participate in the development of AI, ML, and statistics models. Furthermore, you’ll have the chance to get your hands dirty with some scorecard modeling using R or Python. The company’s great internal and external continuing education courses are a big plus, too.
What they do: This rapidly expanding startup offers cloud-based analytics products for the insurance sector. Aureus’ AI platform CRUX leverages NLP to discover trends and patterns of client behavior. With its powerful features providing real-time insights, it ultimately boosts customer retention and leads to greater lifetime value.
Where to apply: HQ is in Singapore, but you could opt for the offices in Mumbai and Hartford, as well.
Why work there: Aureus Analytics is definitely on the rise with its recently closed fundraiser of $3.1 million. What comes next for the startup is further expansion in the U.S. market and scale-up of their platform development. Aureus offers plenty of data science career opportunities. Plus, its team promises you’ll have a grand time working with them.
What they do: Care about revolutionizing healthcare with machine intelligence?
That’s exactly what HEALTH[at]SCALE does. This Silicon-Valley-based startup delivers a platform and SaaS applications that aim to “match the world’s patients to the right treatments by the right providers at the right times, at critical points of care”. Their solutions are designed from the ground up and use advanced predictive machine intelligence for maximum operational healthcare impact.
Where to apply: Downtown San Jose – with over 100 restaurants and coffee shops in the area, and just a few minutes away from the Caltrain. Fun!
Why work there: Well, we’re definitely not the only ones who believe HEALTH[at]SCALE is one of the best startups out there. It was recently backed by leading investors, raising $16 million in its Series A funding round. And, when it comes to development opportunities, HEALTH[at]SCALE offers plenty. Working there will give you the chance to learn from prominent faculty members with strong ties to MIT, Harvard, Stanford, and the University of Michigan. You’ll be able to Implement new predictive ML and AI algorithms, extract valuable insights from healthcare datasets, and perform analysis to solve major healthcare challenges. Who said that noble causes can’t be exciting?
This wraps up our list of the best startups to work for in 2023.
Now you’re in-the-know about what Cinnamon, Oden Technologies, Spoonshot, and all the other super-hero teams above have to offer. So, no matter if you choose to apply for a data science job in a startup, or you aim for that corner office in a large corporation, we’re confident you’ll make an informed decision.
With this article, we hope we’ve inspired you to keep your options open. This will help you explore all career opportunities before making up your mind about your professional future. There isn’t only one right way to start your data science career. However, if you choose to go off the beaten path, you may just find what you’re looking for.
In the meantime, if you’re considering a career in data science but you feel you’re not exactly where you need to be in terms of technical knowledge and specifics, you can check out our super helpful resource Starting a Career in Data Science: The Ultimate Guide.
Keep learning & growing and good luck!