Data Scientist

Basic Information

Pollfish, a Prodege, LLC company , is an online market research survey platform where data driven brands bring market research in-house for faster and smarter decision making. We have a proprietary network of 250M consumers/year which enables companies to connect with and understand real consumers worldwide in a fast, easy and cost-effective way.

We are currently looking for an experienced Data Scientist to join our team, which is based in Athens.

The position applies statistical and machine learning techniques to large-scale behavioral and transactional data to improve ranking, recommendation, and yield optimization. While this role partners closely with Engineering and ML Engineering teams, it does not own production deployment, infrastructure, or MLOps. 

Responsibilities

Business Translation & Modeling Framework Design:

• Partner with Product and other business stakeholders to frame business problems into well-defined modeling objectives and hypotheses.
• Select appropriate modeling techniques (e.g., classification, regression, deep learning, reinforcement learning) based on use case and data characteristics.
• Define success metrics and evaluation criteria that align model performance with business impact.
• Document modeling assumptions, tradeoffs, and intended use to ensure clarity, transparency, and alignment across teams

Data Analysis & Feature Development

• Perform analysis on large-scale behavioral and transactional datasets to identify patterns, drivers, and potential predictive signals
• Engineer features from user behavior, lifecycle activity, offer attributes, and revenue data to support modeling objectives
• Collaborate with ML team to ensure features properly registered within feature store

Model Development & ML Collaboration:

• Leverage appropriate modeling frameworks and packages to build high performing predictive models
• Perform model tuning, validation, and comparison using appropriate metrics, cross-validation, and offline testing frameworks
• Interpret model outputs to assess business relevance, identify strengths and limitations, and validate against observed behavior
• Leverage appropriate frequentist and Bayesian approaches to measure model performance and define strategies for balancing exploration and exploitation
• Document modeling approaches, performance results, and learnings in model cards to support reuse, iteration, and long-term knowledge building
• Enable ML team to deploy models; collaborate on retraining and maintenance plans

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field
• Fluency in English
• 4+ years of experience performing deep data analysis and training machine learning models
• Strong foundation in machine learning and statistical modeling (classification, regression, ranking, optimization)
• Experience with ranking, recommendation systems, and personalization models
• Ability to apply AI and machine learning tools responsibly in support of predictive modeling, analysis, experimentation, and solution development, including validating outputs, documenting assumptions, and adhering to company security and confidentiality standards.
• Fluency in Python and common ML libraries (scikit-learn, XGBoost/LightGBM, PyTorch, or TensorFlow)
• Fluency in SQL and ability to work with large, event-level datasets in data warehouse environments (e.g., Snowflake, BigQuery, Redshift)
• Experience with feature engineering, model evaluation, and performance diagnostics
• Strong analytical reasoning and ability to translate business questions into modeling approaches
• Clear communication skills, particularly in explaining model results and tradeoffs to non-technical stakeholders
• Understanding of ML Ops concepts and the ability to collaborate effectively with ML Engineering and ML Ops teams
• Excellent attention to detail
• Proficiency in critical thinking and problem-solving

Good to Have

• Hands-on experience managing ML deployments and designing feature stores and registries
• Experience with AI/ML frameworks such as LangChain, LLMs, and HuggingFace
• Worked with distributed data processing frameworks (Spark, Ray, Flink, Trino).
• Experience in loyalty programs or performance marketing or market research
• Experience with contextual multi armed bandit algorithms or reinforcement learning
• Understanding of Bayesian statistics inference (e.g., PyMC)

Benefits

• An attractive salary package
• Part of an innovative Global Tech Company
• Meal Coupons - Monthly
• Gym Subscription
• Private Health Insurance
• Weekly Office Events - Catered Lunch and Breakfast
• Company Outings & Quarterly Events
• Mental Health Benefits - Wellness Coach App Subscription
• Great office location in the city center - Parking slots available
• Quarterly Charitable Giving Allowance
• Peer recognition Allowance