Senior Data Scientist
Haystack News · Fort Lauderdale Office
Extracted from the posting
Senior Data Scientist at Haystack News building statistical and machine learning models to improve content discovery and user engagement, with causal inference and A/B testing to measure product impact. Works with ML engineers to move models into production, and builds features using text and multimodal embeddings and GenAI. Stack: Python (pandas, NumPy, statsmodels, scikit-learn, LightGBM, XGBoost), SQL (Postgres, Snowflake); PyTorch/TensorFlow, dbt and Airflow preferred.
Haystack News, the number one destination for news on streaming platforms, is looking for a Sr Data Scientist to join our team. Haystack is trusted by over 30 million viewers and is among the fastest-growing TV news companies in the world.
Join our team at Haystack News as a Senior Data Scientist and become a pivotal force in redefining user experiences through cutting-edge algorithm enhancements. In this role, you'll leverage your advanced statistical analysis, modeling, causal inference, experimental design (A/B testing) and data analytics expertise to drive substantial improvements in user engagement and retention, directly impacting our product's success. This is an exceptional opportunity to showcase your robust problem-solving capabilities and to thrive in a collaborative environment, working alongside a team of passionate professionals dedicated to innovation and excellence. Be part of a dynamic workplace where your contributions make a meaningful difference and help shape the future of news consumption.
MINIMUM QUALIFICATIONS
- PhD or M.S. in Computer Science, Mathematics, Electrical Engineering, Statistics, Economics or Operations Research with 5+ years of professional experience in data science, machine learning or related quantitative field
- 3+ years of professional experience with large-scale online ranking/recommender systems (for news feeds, shopping, ads, music, etc).
- Deep expertise in statistical inference and experimental design: hypothesis testing, power/sample size calculations, variance reduction, etc.
- Proficiency in causal inference methods to measure product impact.
- Proven ability to translate offline analysis into product decisions and measurable improvements in online metrics.
- Fluency in the Python analytics stack (pandas, NumPy), statistical modeling (statsmodels or scikit-learn) and machine learning packages such as LightGBM and XGBoost.
- Strong experience with SQL (e.g. postgres, snowflake, etc).
PREFERRED QUALIFICATIONS:
- Experience working on consumer-facing products with millions of users.
- Hands-on experience with orchestration/transformation tools (e.g. dbt and Airflow).
- Experience with deep learning and being familiar with tools such as PyTorch or TensorFlow.
- Hands-on development of products/tools incorporating GenAI, LLMs, RAG, and/or Agents.
RESPONSIBILITIES
- Build statistical and machine learning models to improve content discovery and user engagement.
- Work closely with ML engineers to translate models and insights into production systems.
- Have curiosity and apply analytical skills to dive deep into data to find key insights that would impact the business.
- Apply causal inference methods to understand the impact of potential product changes.
- Define and build new ML features using text and multimodal embeddings and GenAI.
- Validate offline learnings with online outcomes through AB testing. Design, execute, and analyze experiments to prove product change attribution.
