Sr. Data Scientist (AI & ML)

Overview

Sr. AI Engineer

GenAI Squad

• , your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data.
• You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers.
• You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.
• Many of our initiatives will focus on leveraging Generative AI for tasks such as
• data enrichment, smart content understanding
• , and
• automated decision-making
• to enhance user experiences and business operations.
• ****Responsibilities****
• Leveraging ambiguous business problems as opportunities to drive objective criteria using data.
• Solving complex business problems using the simplest, most appropriate algorithms to deliver business value.
• Designing and implementing effective and impactful machine learning and generative AI systems in production.
• Developing a deep understanding of the product experiences and business processes that make up your area of focus.
• Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.
• Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.
• Working closely with product and business teams to identify important questions that can be answered effectively with data.
• Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.
• Designing, planning, and analyzing experiments (A/B and multivariate tests).
• Supporting product and business managers with KPI design and goal setting.
• Mentoring other data scientists in their growth journeys.
• Contributing to improving our ways of working, our tooling, and our internal training programs.
• ****Qualifications****

Requirements

• ****Technical Experience****
• Experience in machine learning, generative AI, deep learning, recommendation systems, pattern recognition, data mining, and artificial intelligence.
• Deep knowledge and experience in ML and GenAI frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch, Hugging Face Transformers, LLM fine-tuning).
• Excellent SQL.
• Competence with reproducible data analysis using Python or R.
• Familiarity with data modeling and dimensional design.
• Strong command over the entire data lifecycle, including problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.
• Familiarity with different types of analysis, including descriptive, exploratory, inferential, causal, and predictive analysis.
• Deep understanding of various experiment design and analysis workflows and the corresponding statistical techniques.
• Familiarity with product data (impressions, events, etc.) and product health measurement (conversion, engagement, retention, etc.).
• Experience with LLMs and NLP-based solutions for data enrichment and smart automation is a plus.
• Familiarity with BigQuery and the Google Cloud Platform is a plus.
• Data engineering and data pipeline development experience (e.g. via Airflow) is a plus.
• ****Qualifications****
• Bachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.
• 5+ years of experience working in data science, machine learning, and Gen AI.
• Experience doing data science in an online consumer product setting is a plus.
• A good problem solver with a ‘figure it out’ growth mindset.
• An excellent collaborator, and communicator.
• A strong sense of ownership and accountability.
• A ‘keep it simple’ approach to #makeithappen.