Forward Deployed Data Scientist

About Translated

Translated is a leading provider of AI-powered language solutions. Founded in 1999 by a linguist and a computer scientist, we are on a mission to allow everyone to understand and be understood in their own language.

We envision a world where people from different cultures can communicate seamlessly, gaining unprecedented access to knowledge, cultural exchange, and opportunity. To make this possible, we combine proprietary translation AI (Lara Translate) with advanced text, audio, and video translation technologies (Matecat, Matesub, and Matedub) and the worldu2019s largest network of vetted, native-speaking language professionals.

We welcome complex technical challenges from our customers and engineer tailored solutions that often become part of our core products, whether integrated into our enterprise localization platform, the tools designed to support translators, or Lara Translate, our online AI translator for teams and individuals.

Everything we build reflects a simple principle: technology should amplify human potential, not replace it.

We believe in humans.

We are looking for a Forward Deployed Data Scientist to work closely with our customers, product teams, and leadership, transforming complex business challenges into data-driven solutions.

The ideal candidate combines strong analytical and technical skills with business acumen and the ability to work directly with stakeholders. You will investigate customer and product data, develop analyses and models, and help deploy solutions that generate measurable business impact.

The Role: Forward Deployed Data Science

Forward Deployed Data Scientists operate at the intersection of data science, product, engineering, and customer success.

You will collaborate directly with Translatedu2019s enterprise customers and internal teams to understand their objectives, investigate their data, identify opportunities, and develop solutions tailored to their operational needs. These solutions may include analytical models, forecasting systems, performance metrics, experiments, dashboards, and data products.

Rather than working only on predefined datasets or isolated research questions, you will follow projects through their complete lifecycle: from problem definition and data discovery to implementation, validation, deployment, and communication of results.

You will gradually develop a deep understanding of Translatedu2019s business, products, and technology, working across areas such as translation quality, operational efficiency, customer behavior, demand forecasting, marketing performance, and financial outcomes.

Successful projects may become reusable capabilities integrated into Translatedu2019s products, enterprise platform, or internal decision-making systems.

Responsibilities

• Work directly with customers and internal stakeholders to understand business objectives and translate them into well-defined data problems
• Identify, access, and evaluate relevant internal and external data sources
• Conduct initial data investigations and exploratory data analysis
• Develop metrics, statistical analyses, machine learning models, and other data-driven solutions
• Design experiments and measurement frameworks to evaluate product and business initiatives
• Analyze customer behavior, operational performance, translation quality, revenue, costs, and other key business indicators
• Build prototypes and collaborate with engineering teams to turn successful analyses into reliable production solutions
• Create dashboards, reports, and visualizations that make complex findings accessible and actionable
• Present recommendations and results clearly to technical teams, business stakeholders, leadership, and customers
• Define success criteria, measure outcomes, and continuously improve deployed solutions
• Collaborate with product managers, software engineers, AI researchers, sales teams, and customer-facing teams
• Help develop reusable analytical methods, tools, and best practices across the company
• Stay informed about developments in data science, machine learning, analytics, and applied AI

Requirements

• 3+ years of professional experience in Data Science, Data Analytics, Applied Machine Learning, or a related quantitative role
• Strong knowledge of statistics, probability, and experimental design
• Excellent programming skills in Python
• Strong experience with SQL and working with large, complex datasets
• Experience with data exploration, statistical modeling, machine learning, and model evaluation
• Ability to transform ambiguous business questions into structured, measurable analytical problems
• Experience defining business and product metrics and using data to support decision-ma