At a Glance
- Tasks: Lead the development of next-gen AI solutions and machine learning models.
- Company: Join Cint, a leader in market research and synthetic intelligence.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Make a real impact on AI technology that shapes market research.
- Qualifications: 5+ years in Data Science, strong skills in Generative AI and LLMs.
The predicted salary is between 70000 - 90000 ÂŁ per year.
As a Senior 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, focusing 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, directly influencing strategic decisions for Cint’s proprietary synthetic data platform.
Responsibilities
- Lead the research, discovery, and development of machine learning models, specifically focused on synthetic row generation, open‑ended text generation, and data augmentation.
- Design and drive advanced statistical methods and complex 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.
- Independently manage complex project planning, development, and maintenance end‑to‑end with minimal supervision.
- Partner with Product, Engineering, and Strategy teams to align technical AI delivery with business goals, ensuring a seamless transition from MVP to scaled integration.
- Create clear, effective prototypes and deliverables that explain and defend complex Generative AI concepts to both technical and non‑technical audiences.
Qualifications Required
- Minimum 5 years of experience in a Data Science capacity, with a track record of leading complex projects.
- A Master's degree (or equivalent) in Statistics, Data Science, or a related quantitative field.
- Deep understanding of Generative AI and LLMs, particularly for applications in text generation and data synthesis.
- Advanced knowledge of statistical techniques: hypothesis testing, sampling theory, experimental design, and causal inference.
- Strong knowledge of a variety of ML techniques (e.g., clustering, regression, neural networks, etc.) and their real‑world trade‑offs.
- Expert proficiency in Python (DS/ML stack) and experience with frameworks used for LLM development and fine‑tuning.
- Advanced SQL skills and experience working with large‑scale databases.
- Ability to research and adopt new methods while mentoring junior colleagues on their application.
Essential Qualities
- Highly accountable self‑starter and quick learner, consistently motivated to deliver high‑quality, impactful results.
- Strong data‑driven mindset with the ability to translate abstract business requests into actionable AI initiatives and solutions.
- Excellent written and verbal communication skills, with the ability to explain and defend complex AI concepts to non‑experts.
Nice to Have
- Direct experience with Synthetic Data Generation techniques and the evaluation of synthetic data quality/utility.
- Experience with Prompt Engineering, RAG (Retrieval‑Augmented Generation), or fine‑tuning open‑source LLMs for open‑end generation.
- Experience with probabilistic modeling, or advanced profiling techniques.
- Familiarity with online market research or survey exchange platforms.
- Experience using Databricks, Spark, or PySpark for large‑scale workflows.
Senior Data Scientist (AI & Synthetic Intelligence) employer: Cint
Contact Detail:
Cint Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist (AI & Synthetic Intelligence)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with Cint employees on LinkedIn. A friendly chat can sometimes lead to opportunities that aren’t even advertised!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and data science. This gives you a chance to demonstrate your expertise in LLMs and synthetic intelligence directly.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical teams.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Cint team.
We think you need these skills to ace Senior Data Scientist (AI & Synthetic Intelligence)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Senior Data Scientist. Highlight your experience with AI, LLMs, and any relevant projects you've led. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you the perfect fit for Cint. Let us know what excites you about the role and our mission.
Showcase Your Projects: If you've worked on any cool data science projects, especially those involving synthetic intelligence or machine learning, make sure to mention them. We love seeing real-world applications of your skills!
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Cint
✨Know Your AI Stuff
Make sure you brush up on your knowledge of Generative AI and Large Language Models. Be ready to discuss specific projects you've worked on, especially those involving text generation and data synthesis. This will show that you not only understand the theory but also have practical experience.
✨Showcase Your Statistical Skills
Prepare to talk about advanced statistical techniques like hypothesis testing and experimental design. Have examples ready where you've applied these methods in real-world scenarios. This will demonstrate your ability to validate models and drive complex experiments.
✨Communicate Clearly
Since you'll need to explain complex AI concepts to non-technical audiences, practice simplifying your explanations. Use analogies or straightforward language to convey your ideas. This will highlight your communication skills and your ability to bridge the gap between technical and non-technical teams.
✨Be a Self-Starter
Cint values accountability and independence, so be prepared to discuss how you've managed complex projects with minimal supervision. Share specific examples of how you've taken initiative in past roles, particularly in developing high-impact solutions that align with business goals.