supertype consultancy

Data Science Consulting

Enterprise level data science consultancy and services from Supertype

Consultation

Guided advisory and consultancy on your data and analytics infrastructure, by machine learning engineers familiar with your business landscape.

Augmentation

An embedded model or a managed services model, where Supertype acts as your extended data science team throughout the engagement.

Expertise Development

A long-term approach to competencies development, with assistance on recruitment, talent development, and upskilling existing employees.

3-Stream Approach to Client Success

We like to take a holistic approach, with a consulting framework that emphasises on competencies development through continual knowledge transfer.

analytics consulting services

Holistic Consulting.

Managing an analytics problem results in downstream technical debt that affects your organization’s decision making ability. 

Solving infrastructural problems in your data and analytics stack is often far cheaper.

Consulting
Our data science consultants and solution engineers work with you to identify key problems and opportunities across your organization, and draw out a solution roadmap after careful consideration of your existing infrastructural constraints and resources. Our domain-specific consultants produce recommendations that are effective, focused and principled.

Augmentation
When you need an embedded team to be deeply immersed within the problem sphere and your data analytics infrastructure. A seamless way to extend your data science team to include missing competencies or complementary engineering dimensions.

Upskill
Maximise knowledge transfer from our team to yours through a series of workshops, and active assistance across the human capital functions — recruitment, talent development and continual mentoring by our data scientists.

Don't stop at Presentation Slides.

Full range of consulting services suitable for enterprises large and small

MLOps & Prototyping

Suitable for companies looking to build out a minimum viable product or machine learning model.

Data Scientists for Hire

Fastest way to add a few extra hands onto your project, accelerating the ideation to deployment cycle.

Managed Development

Good fit for enterprises in the midst of establishing their data science and engineering team.

Analytics Automation

A done--for-you service for companies to extract key insights from a multitude of first- and third-party data sources.

Corporate Training

Ideal for companies looking to upskill their core team members with data science, programming. and engineering skills.

Post-consultation Hand-off

Typically included in any of Supertype's consulting service, with the aim of maximising long-term knowledge transfer.

70 %
of data science projects fail.

According to Gartner, up to 90% of data science projects are met with failure due to a mismatch in competencies and expectations. On one end of the spectrum companies surveyed responded that their data scientists face insurmountable challenges in bringing their research into production. On the other hand, software developers tasked with productionizing data science models consistently responded that the models developed by the scientists were far from the required standard beyond the most basic of prototypes.

full cycle data science consultancy

Full Cycle Data Science Consulting

Data analytics services are not standalone functions. 

data scientist vs data engineers

The massive divide between data professionals who consider themselves stronger on the research-science axis and those who align themselves on the software-engineering further adds to this friction. A high proportion of these failure also cite a lack of business acumen, or domain knowledge, from both the data scientists and the software engineers, in why a promising project falls short of the expected outcome.

Learning from these past failures, Supertype is created from the ground up by deeply coupling the science and engineering domains, advocating that data science teams should embrace a more cross-disciplinary, integrated paradigm when it embarks on a new project.

As a full cycle data science consultancy, we re-orientate the conversation around quantifiable business goals — committed to seeing a project through from model research and prototyping, to. live deployment. At Supertype, state-of-the-art machine learning isn’t a goal, but means to an end.

Schedule a Demo

Supertype employs a consulting model that begins with the identification of business value and ends with an evaluation of our key deliverables against these business values. We’re not a research firm. We’re not a software house. We’re not in the business of making presentation slides before handing it off to you.

 

This full cycle data science model re-orientates the conversation to center around obtainable, quantifiable business goals for your organization. Schedule a discussion with us to explore opportunities of working together.

Your work email, so we can reach you. We respect your privacy and will not add you to any mailing list.

Enterprise consulting case study

Data science consultancy doesn't need to be daunting or complicated. Read on to learn more about our past client engagement.

Creadits x Supertype

Supertype’s data scientists and Creadits combined to produce advertising creatives that are 40% more performant, powered by data

Opera x Supertype

Learn how Supertype’s data scientists took AdColony (by Opera) advertising operations and monetisation to the next level using a range of machine learning techniques

Adaro Mining x Supertype

How Supertype develop an end-to-end analytical infrastructure to facilitate real-time analytics and water level prediction for Adaro, a regional leader in coal mining and related operations.

supertype summary

From Raw Data to Insights packaged in a PDF

Not ready for a get on the data science consulting journey with us yet? Start with an analytics automation project through Supertype Summary.

frm model analysis

Business Intelligence

Custom analytics dashboard that brings together data from your user acquisition team, monetization team, in-app analytics SDK and everything else. Includes an audit of your existing processes, design, planning and development of your own analytics system. One-time pricing.