Lead Decision Scientist, Machine Learning Engineer, UK 2024 Full Time

Aimpoint Digital

Aimpoint Digital is a premier analytics consulting firm with a mission to drive business value for clients through expertise in data strategy, data analytics, decision sciences, and data engineering and infrastructure. This position is within our decision sciences practice which focuses on delivering solutions via machine learning and statistical modelling.

What you will do

As a part of Aimpoint Digital, you will focus on enabling clients to get the most out of their data. You will work with all levels of the client organization to build value driving solutions that extract insights and then train them on how to manage and maintain these solutions. Typical solutions will utilize machine learning, artificial intelligence, statistical analysis, automation, optimization, and/or data visualizations. As a Lead Data Scientist, with a Databricks focus, you will be expected to work independently on client engagements, take part in the development of our practice, aid in business development, and contribute innovative ideas and initiatives to our company. As a Lead Data Scientist you will:

1. Become a trusted advisor working with clients to design end-to-end analytical solutions.
2. Work independently to solve complex data science use-cases across various industries.
3. Design and develop feature engineering pipelines, build ML & AI infrastructure, deploy models, and orchestrate advanced analytical insights.
4. Write code in SQL, Python, and Spark following software engineering best practices.
5. Collaborate with stakeholders and customers to ensure successful project delivery.

Who we are looking for

We are looking for collaborative individuals who want to drive value, work in a fast-paced environment, and solve real business problems. You are a coder who writes efficient and optimized code leveraging key Databricks features. You are a problem-solver who can deliver simple, elegant solutions as well as cutting-edge solutions that, regardless of complexity, your clients can understand, implement, and maintain. You genuinely think about the end-to-end machine learning pipeline as you generate robust solutions. You are both a teacher and a student as we enable our clients, upskill our teammates, and learn from one another. You want to drive impact for your clients and do so through thoughtfulness, prioritization, and seeing a solution through from brainstorming to deployment. In particular you have these traits:

1. Databricks experience is required.
2. Degree in Computer Science, Engineering, Mathematics, or equivalent experience.
3. Experience with building high quality Data Science models using Databricks ML to solve client’s business problems.
4. Experience in deploying models via model serving within Databricks.
5. Experience with managing stakeholders and collaborating with customers.
6. Strong written and verbal communication skills required.
7. Ability to manage an individual workstream independently.
8. 3+ years of experience developing ML models in any platform (Azure, AWS, GCP, Databricks etc.).
9. Ability to apply data science methodologies and principles to real life projects.
10. Expertise in software engineering concepts and best practices.
11. Self-starter with excellent communication skills, able to work independently, and lead projects, initiatives, and/or people.
12. Willingness to travel.

Preferred Qualifications

1. Consulting Experience.
2. Databricks Machine Learning Associate or Machine Learning Professional Certification.
3. Familiarity with traditional machine learning tools such as Python, SKLearn, XGBoost, SparkML, etc.
4. Experience with deep learning frameworks like TensorFlow or PyTorch.
5. Knowledge of ML model deployment options (e.g., Azure Functions, FastAPI, Kubernetes) for real-time and batch processing.
6. Experience with CI/CD pipelines (e.g., DevOps pipelines, Git actions).
7. Knowledge of infrastructure as code (e.g., Terraform, ARM Template, Databricks Asset Bundles).
8. Understanding of advanced machine learning techniques, including graph-based processing, computer vision, natural language processing, and simulation modeling.
9. Experience with generative AI and LLMs, such as LLamaIndex and LangChain.
10. Understanding of MLOps or LLMOps.
11. Familiarity with Agile methodologies, preferably Scrum.

We are actively seeking candidates for full-time, remote work within the US, the UK, or Colombia.