Cint

Research Technology (ResTech)

DataScientist(AI&SyntheticIntelligence)

Barcelona, Spain FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for mid candidates.

The Brief

“Data Scientist (AI & Synthetic Intelligence) at Cint. Skills: Generative AI, LLMs, Python, SQL. Contribute to research, discovery, development of ML models. Execute statistical tests and experiments”

What You'll Achieve.

deliver high-quality, impactful results

Industry & Context.

Research Technology (ResTech)
Problems you'll solve

data-driven mindset with the ability to translate abstract business requests into actionable AI initiatives and solutions

What They're Looking For.

Must Have

Minimum 2-4 years of experience in a Data Science capacity, experience delivering end-to-end data science solutions, Master's degree (or equivalent) in Statistics, Data Science, or a related quantitative field, Deep understanding of Generative AI and LLMs, Advanced knowledge of statistical techniques, knowledge of a variety of ML techniques, Expert proficiency in Python (DS/ML stack), Advanced SQL skills, experience working with large-scale databases, Ability to research and adopt new methods

Nice to Have

Direct experience with Synthetic Data Generation techniques, evaluation of synthetic data quality/utility, Experience with Prompt Engineering, RAG (Retrieval-Augmented Generation), fine-tuning open-source LLMs for open-end generation, Experience with probabilistic modeling, advanced profiling techniques, Familiarity with online market research or survey exchange platforms, Experience using Databricks, Spark, PySpark for large-scale workflows

What You'll Do.

Contribute to research

development of ML models

Execute statistical tests and experiments

Develop logic for boosting capabilities

Design and refine profiling taxonomies

Manage technical workflows and development cycles

Create prototypes and deliverables

How You'll Work.

Team & Collaboration

Collaborating closely with Product and Engineering teams; collaborating with Engineering to integrate models; Collaborate with Product and Engineering teams

Communication Scope

Create clear, effective prototypes and deliverables that explain and defend complex Generative AI concepts; Excellent written and verbal communication skills; communicate technical findings clearly

Process & Methodology

Manage technical workflows and development cycles

Full Job Description

Who We Are Cint is a pioneer in research technology (ResTech). Our customers use the Cint platform to post questions and get answers from real people to build business strategies, confidently publish research, accurately measure the impact of digital advertising, and more. The Cint platform is built on a programmatic marketplace, which is the world’s largest, with nearly 300 million respondents in over 150 countries who consent to sharing their opinions, motivations, and behaviours. We are feeding the world’s curiosity! As a Data Scientist at Cint, you will play a pivotal role in developing next-generation AI solutions that power our product portfolio. Collaborating closely with Product and Engineering teams, you will bridge the gap between traditional research data and synthetic intelligence. You will focus on the research, validation, and delivery of models—including Large Language Models (LLMs)—that augment high-quality human signals across the Cint Exchange. This role involves advanced data mining, robust data validation, and the development of sophisticated statistical and machine learning methodologies. The ideal candidate can independently research, develop, and maintain high-impact solutions that align Cint’s AI capabilities with market research trends, contributing to the technical roadmap for Cint’s proprietary synthetic data platform. Responsibilities * Contribute to the research, discovery, and development of machine learning models - specifically focused on synthetic row generation, open-ended text generation, and data augmentation. * Execute statistical tests and experiments to validate LLM performance and synthetic modeling hypotheses. * Develop logic for on-demand and dynamic boosting capabilities, collaborating with Engineering to integrate these models into Cint Exchange fielding workflows. * Design and refine sophisticated profiling taxonomies, leveraging large-scale datasets to create syndicated audiences. * Manage technical workflows and develop

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