Data Scientist

About us…

We’re a global intelligent automation consultancy in a period of hyper growth. Founded in 2020 in the UK, TQA has raised $20m in Series A and expanded to global offices in the US, Argentina, Romania and the Philippines. We’ve got a team of 140 people across the globe of extremely talented individuals who love to solve problems together. We passionately believe that automation has the power to expedite business transformation, enhance enterprise value and deliver a positive impact on people’s lives.

We’re looking for a highly skilled Principal Data Scientist to play a pivotal role in maintaining, upgrading and scaling our AI-powered systems; integrating these models into business workflows to deliver transformative, real-world applications and helping our clients thrive. If you’re passionate about Machine Learning, and thrive in a fast-paced environment - we want to hear from you.

This role will involve a diverse range of responsibilities that may evolve over time, requiring flexibility and adaptability as the business and its projects grow and change, offering the opportunity to work across multiple areas of data science, cloud infrastructure, and machine learning.

About you…

6+ years Data Science consultancy experience (PhD + 3 years, Masters + 4 years, or Grad + 6 years - the degrees ideally would be Computer Science, Data Science or other STEM):

• 3+ years client-facing experience
• At least two projects delivered into production
• Strong experience conducting Exploratory Data Analyses in customers of multiple different industry types and different types of data. Structured and unstructured, image, natural language, etc
• Experience with supervised, semi-supervised and unsupervised ML
• Able to flex to project and client requirements, which may necessitate pragmatic compromise in order to deliver an outcome
• Knowledge of and use of publicly available accelerators to delivery, such as code repositories that can be used as a base, pretrained models etc.
• Able to use Generative AI models and workloads to accelerate delivery
• Experience with go-to-market offering creation and development, the presales and sales cycles and how to support them technically, and ongoing support of delivered projects

3+ years of experience in team leadership and management:

• Head of/Lead-level positions
• Must have had at least 2 direct reports (ie Line Manager) that were Data Scientists
• Involved in growing teams - experience in hiring, firing, growth areas etc
• Used to collaborating across geographies and timezones, adopting a ‘federated’-type approach - self-contained, but operating within and accountable for delivering against the overall global strategic priorities
• Comfortable with flexing work hours to fit client requirements, such as UK timezones

The ideal candidate will have…

Experience with carrying out Data Science and ML workloads on AWS. These would include:

• Amazon SageMaker (including training jobs, hyperparameter tuning jobs, inference endpoint deployment)
• ‘Core stack’ including Lambdas, S3, ECS etc.
• Data transformation technologies, including Glue/Athena (but not expecting full expertise)
• Strong knowledge of SageMaker Augmented AI and Ground Truth, leveraging its outputs to improve ML models
• Serverless ML design patterns for AWS, including using Lambdas and Step Functions to orchestrate SageMaker

Python open-source Data Science stack, including:

• Plotting: matplotlib, seaborn, plotly etc.
• Data manipulation: pandas, numpy, scipy etc.
• ML/Deep Learning: scikit-learn, pytorch etc.
• Generative AI: OpenAI API usage etc.

Communication skills:

• Able to present technical information to non-technical audiences
• Able to demonstrate art-of-the-possible with SMEs that don’t know what is possible with their data, to understand what data might be available (publicly or otherwise) that the client might not know or think to use
• Able to work with domain experts outside their skillset, which may include Solution Architects, Data Engineers, MLOps Engineers etc
• Able to creatively solve problems, both human and machine, to deliver the greatest change and strongest outcome given the true landscape for a project or series of projects
• Strong English language skills

Experience with taking on, maintaining, supporting and upgrading production codebases

• Experience responding to tickets logged against business-critical systems
• Able to triage issues, and attempt to solve, such as data quality issues affecting the output of a production ML workload
• Able to communicate with and collaborate with experts in other area, such as Data Engineering, Web Development and MLOps, to solve issues that might span across multiple areas

Experience with Databricks to deliver Data Science outputs, ML models and production-grade solutions

• Experience with multiple hyperscalers, especially Azure, and ideally Azure OpenAI
• Strong experience with production, such as understanding how to implement ML into end-user-facing workloads and embedding them in business processes effectively
• PoC to production experience with Generative AI, such as RAG deployment or GPT-X API integration into a user-oriented workflow
• Data Warehouse/Data Engineering technology exposure or experience, such as configuring Databricks from the outset for a new environment

In this role you will…

You will be a key figure in maintaining the technological backbone of the organization. This role involves overseeing the daily operations of computer networks and systems to ensure they run efficiently and securely.

As an IT Administrator, you will handle the upkeep, configuration, and reliable operation of computer systems, particularly multi-user computers such as servers. You will ensure that the internal IT structure of the company remains robust and efficient, handling tasks such as software upgrades, user training, troubleshooting, and network management.

You will also implement and oversee security measures to protect data and manage access controls.

And the most important part of your role is to provide technical support to employees, resolving any IT-related issues quickly and efficiently. You may also be involved in planning and implementing IT policies and procedures to ensure best practices. Lastly, you must stay abreast of new technology trends and be able to work with a variety of technologies and systems.

Sounds good? Here’s an outline of the responsibilities.

Team cultivation (5-10%):

• Oversee the local team development (1:1s etc), hold country-wide DS Huddles to share knowledge and discuss the cutting edge
• Create and refine go-to-market materials and offerings, such as how we will best leverage the Databricks best practices for our clients and how this dovetails into our broader Data offerings (working with the Data Science Director and other Data principals)

Managed service response (5-10%):

• We have signed a Managed Services agreement with a major UK-based company. They have a break-fix with us, however a lot of the issues they report and identify actually stem from underlying data quality issues.
• We want to identify these proactively, but also respond to the client with triaged and catalogued issues
• You would be the main cover for the initial chasing to this identification/deidentification of being or not being a Data quality-related issue, such as a malformed field in a form being parsed as a string instead of an integer - this is simple but difficult to uncover without going through the codebase etc.

Research and development: (10-20%):

• You would be working closely with our local and international teams to create accelerators and other IP that will enhance our offerings to clients
• This involves staying at the state-of-the-art, such as reading and presenting the latest papers in journal clubs, as well as sharing more publicly with blogs and meetups
• TQA understands the need for this to be part of your role officially, and as such it is

Delivery (60-80%):

• For some current and new customers, you would run our AI Advisory and Data Science as a Service delivery models as the key expert DS. Initially, this will involve mostly a sole operation, but in time you will oversee teams of more junior colleagues who will support you across multiple projects.