Machine Learning Specialist

7 days ago

Taguig, National Capital Region, Philippines Thinking Machines Data Science Full time
Company Overview

Thinking Machines Data Science is a technology consultancy that builds AI & data platforms to solve high-impact problems for our clients. Our vision is to create a global hub for data science in Southeast Asia, driving inclusive innovation through diverse teams and care for people.

We're a company of intellectually curious and civic-minded individuals who believe great data science products are built with care for people. To achieve this, we want to hire people who can demonstrate an ability to learn, provide personalized coaching, growth opportunities, and a great working environment to help them grow to world-class professionals.

Job Description

This role offers the opportunity for someone with a strong portfolio of work in machine learning and analytics to collaborate with a high-performance team. The ideal candidate will be creative, think critically, and focus on delivering excellent results. They'll be expected to effectively handle projects from day one, provided with effective guidance as they learn and implement machine learning methods for clients and internal products.

We're a technology consultancy with constantly evolving responsibilities, and the following is an incomplete but representative list of things you can expect to do:

  • Scoping work on ML/analytics use cases: Working with clients to understand their needs and designing quantitative solutions to address those needs using machine learning, analytics, data pipelines, and visualization or other methods.
  • Exploring data and its sources: Looking for patterns and signals in the data, identifying important fields, gleaning insights, and discerning whether machine learning can apply to the problem.
  • Developing and evaluating machine learning models: Feature engineering, experimenting with different model types, choosing the right metrics, measuring performance, analyzing model performance and results (e.g., feature importance, model stability, performance across different groups), etc.
  • Understanding model design and decisions: Explaining how models work under the hood and how a model arrived at a certain prediction, choosing the right model family, and justifying accuracy tradeoffs for faster performance.
  • Implementation strategy and application: Recommending ways that the client can use the model outputs in their business, often involving collaboration with both the client and other Thinking Machines teammates (e.g., Strategists, Business Intelligence Analysts).
  • Research and keeping up with the tech space: Reading through published ML papers and implementing improved versions of their models in new domains.
  • Acquiring, cleaning, and evaluating the integrity of datasets.

In addition, senior ML Consultants are expected to assume technical leadership roles. On projects, they must plan out roadmaps for ML/analytics solutions delivery, own a project's ML/analytics components, and serve as a point-person for client interactions regarding these components. They must offer sound technical guidance to junior staffers and the rest of the project team members.

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