Analyst within Credit Risk Management team identifying credit segmentation opportunities using statistical methods. Collaborating with teams to enhance credit decision process and policies.
SF
Hybrid Senior Data Scientist, Experimental Design, Statistical Inference
Posted 3 weeks ago
About the role
- help develop and drive strategic analytical initiatives
- contribute to improving our use of experimentation and statistical methods
- lead designs of complex experiments across the Fidelity Wealth organization
- serve as a thought leader
- help drive culture and governance to help us further in our growth as a test and learn driven organization
- be a key member of our team driving the future state of methodology in our in-house measurement platform
- help enhance platform statistical methods
- work with engineering on implementation
- lead education for adoption
Requirements
- PhD (preferred) or Masters in a quantitative/field such as Statistics, Biostatistics, quantitative Social Science (including but not limited to economists), Epidemiology, Public Health, Engineering, Computer Science, or related field
- 3-5 years post PhD or 7-10 post Masters of proven experience applying experimental design and statistical inference to academic and non-academic problems
- Strong understanding of core concepts in experimental design including randomization, blocking, factorial designs, cluster designs
- Expertise in using and explaining statistical inference methods for experimental and quasi-experimental circumstances
- Statistical experience using a mix of modeling and inference methods with cross-sectional, longitudinal and time-series data
- Experience developing experimental designs; ideally in a marketing, web, social media, industrial, pharma, or other corporate context
- Candidate would, ideally, have some experience in A/B testing, email experimentation, and similar problems in a corporate setting
- Experience working on cross-disciplinary teams that include engineers, scientists, and non-technical team members
- Demonstrated proficiency in programming, modeling and analysis using Python or R
- Familiarity with core libraries in either language
- Experience querying and analyzing data with contemporary databases such as Snowflake using SQL (and scripting languages as needed)
- Some experience using data visualization tools or libraries
Benefits
- comprehensive health care coverage and emotional well-being support
- market-leading retirement
- generous paid time off and parental leave
- charitable giving employee match program
- educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career
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