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Join a strong community where all we do is care-for the children and families we serve every day, as well as for our dedicated team members. Our people are our best asset. We listen and we know what you're looking for:
You want benefits. We support you with a minimum 50% childcare discount, immediate access to benefits, innovative health programs, 401(k) company match, and much more.
You want balance. We offer flexible schedules that work for you, no nights or weekends, the ability to bring your children to work with you, and paid time off.
You want opportunity. We invest in your future with ongoing training, tuition reimbursement, credential assistance, and our unique Master Teacher Program.
You want recognition. We provide a positive, fun workplace where employees are appreciated.
We are seeking a highly analytical and results-oriented Senior Data Scientist to drive experimentation and decision science initiatives that inform key business decisions. This role will partner closely with business stakeholders to design, execute, and evaluate experiments, apply advanced statistical and causal inference methods, and deliver actionable insights that improve business outcomes.
As a senior individual contributor, you will independently lead analytics projects from problem definition through measurement and recommendation. You will help translate business questions into testable hypotheses, create rigorous treatment and control frameworks, and communicate results in a way that enables confident decision-making.
Key Responsibilities
Lead end-to-end experimentation and decision science projects, from framing business questions through communicating results and recommendations.
Design, execute, and analyze experiments, including A/B tests, quasi-experiments, matched-market tests, and causal inference studies.
Advise business partners on experimental design, sample size determination, power analysis, treatment and control selection, and measurement plans.
Develop matched-control methodologies and statistical frameworks using Python, R, SQL, and other analytics tools.
Apply advanced statistical techniques, regression modeling, predictive analytics, and machine learning where appropriate to support business decisions.
Partner with stakeholders to translate business challenges into analytical solutions and measurable outcomes.
Communicate findings clearly to technical and non-technical audiences, including practical implications, risks, limitations, and recommended actions.
Build repeatable analytical workflows and maintain high standards for code quality, reproducibility, and documentation.
Provide technical guidance and support to analysts and junior data scientists on experimental design and statistical methods.
Contribute to experimentation and decision science best practices within the analytics organization.
Required Qualifications
Master's degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, or a related field with 2-4 years of experience; or Bachelor's degree with 4-6 years of experience in experimentation (mandatory), and data science or advanced analytics.
Strong expertise in all of the following:
Statistical and inferential analyses (advanced/expert level knowledge)
A/B testing and experimentation (advanced/expert level knowledge)
SME on sample sizing, market selection, creating matched controls using tools like R or Python
Regression and predictive modeling
Machine learning methods (supervised and unsupervised)
Big data analysis (e.g., distributed computing, PySpark)
Proven experience delivering experimentation and decision science projects end-to-end, including scoping, execution, stakeholder engagement, and presenting results.
Proficiency in Python/PySpark, R, and SQL.
Strong business acumen with the ability to connect analytical work to strategic and operational outcomes.
Excellent communication skills, with demonstrated ability to influence senior partners and simplify complex concepts.
What We're Looking For
A hands-on data scientist with strong expertise in experimentation, causal inference, and statistical analysis. The ideal candidate combines technical rigor with business curiosity and can independently translate business questions into testable hypotheses, robust experiments, and actionable recommendations. They are comfortable working cross-functionally, communicating findings to non-technical audiences, and driving measurable business impact through data-driven decision-making.
Learning Care is an equal opportunity employer and will not discriminate against an employee or applicant based on race, color, religion, national origin or ancestry, sex, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status or any other protected status under federal, state, or local law.
