Job description

Haystack News haystack.tv, 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.

Requirements

Must-haves

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).
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.

Nice-to-haves

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.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningpythonsqlpostgresml

Platform: ashby
Effort: quick