Senior Data Scientist
At a glance
Senior Data Science role at Haystack News. Fort Lauderdale · full-time · no salary stated · we estimate $150,000–$205,000 across the United States.
Haystack News has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Build statistical and machine learning models that help users find content and stay engaged
- Turn model outputs and analytical findings into production systems alongside machine learning engineers
- Use causal methods to assess proposed product changes and their effects
- Create machine learning features from text, multimodal embeddings and generative AI
- Design and evaluate experiments, using online results to check offline findings and attribute product changes
What you bring
- A master’s or doctoral degree in a listed quantitative field, plus at least five years in data science, machine learning or a related area
- At least three years working on large-scale ranking or recommendation systems, such as news feeds, shopping or ads
- Strong grounding in statistical inference, experimental design and causal methods for measuring product impact
- Experience translating offline analysis into product choices and measurable online results
- Fluency in Python analytics tools, machine learning packages and SQL
Who this fits
This senior role suits someone with substantial data science experience, particularly in ranking or recommendation systems and product experimentation. The position is hybrid in Fort Lauderdale.
From the employer
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.
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