Staff Data Scientist (AI & ML)
Skills
About This Role
Overview
- 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.
- strong>Technical Experience/strong>
- 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.
- 7+ 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.
- An excellent communicator.
- A strong sense of ownership and accountability.
- A keep it simple approach to #makeithappen.
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