Data Scientist, Experimentation

Key Skills

Python Programming, SQL, A/B Testing, Keras software library, Pandas, PyTorch, TensorFlow, Scikit-learn, matplotlib, Experimentation, Large data sets

Job Description

Dow Jones is looking for a Data Scientist to join our experimentation and data science teams. This Data Scientist will focus on how we drive decisions in our products and member experiences through experimentation, working with our teams from concept inception to long term delivery. The outcome of this work will have significant impact for Dow Jones’s brands like The Wall Street Journal, MarketWatch, and Barron’s.

This is an exciting time for experimentation science at Dow Jones! Building on a proven track record, we are looking to expand the amount of experiments we run and look for opportunities where cutting edge data science approaches can drive success. The expansion of our experimentation work is significant and this role will be a key partner for our teams.

Scientific rigor and process is at the heart of what we do. Top candidates will have experience running A/B experiments and/or a strong track record of critical and scientific thinking. This role will interface with our experimentation, product, and leadership teams, so an ability to communicate effectively with technical and non-technical audiences is needed. Top candidates will be an active and valued thought leader in shaping the work teams are doing.

This role will help to deliver on the following and more:

• Consultation on Experiment Strategy: Working with product managers, you will analyze data to identify opportunities for growth and inform experiment hypotheses.
• Sample Size Planning: For every experiment, deliver statistical sample size analysis and planning to help ensure that experiments produce actionable results, as well as ensuring that we are testing as many informative variations as we can.
• Post-Test Analysis: Support product managers on post-test analysis, focusing on statistical significance calculations and segmentation of data. This work may also require causal analyses and modeling.
• Larger-Scale Experimentation Projects: Working with our engineers and experimentation leadership, you will be a key contributor to evolving the technology and processes we use, to ensure we are meeting the needs of our experimentation program and allowing us to continue innovating.
• Helping to drive technical excellence: As Dow Jones continues to build out our experimentation efforts, this role can help us focus in on where we might use different testing strategies, e.g., Bayesian or machine learning driven, that could unlock more efficiency or better testing strategy and processes.

Core requirements:

Data Science candidates will have a minimum of 1+ years of experience executing and leading data science projects. Candidates with a PhD in a quantitative field will require less experience, while those with B.S. or M.S. degrees may require more. The amount of experience needed will be assessed based on the depth of previous data work, knowledge of data science, understanding of statistical methods, and the nature of previous project/product deliverables.

Skills, experience, and knowledge:

• Very strong communication skills and - (preferred) - experience working with product managers and owners.
• Clear understanding of A/B testing, power analyses, and how these may relate to short term and long term web/app usage.
• Knowledge of Python and the Python data stack - Scikit Learn, Pandas, Matplotlib, etc. Knowledge of packages in the Tensorflow/Keras/Pytorch space is a plus.
• Experience with SQL and working with large tabular data.
• Understanding of casual and quasi-experimentation modeling, and its limit ations, would also be preferred in top candidates.

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All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, protected veteran status, or disability status. EEO/AA/M/F/Disabled/Vets .