below marketmost similar roles pay hereabove market
This role pays more than
85%
of similar roles. Most pay
$141,225–$211,750
— the blue band above.
At the midpoint, this role pays about
$231k
versus about
$176k
for comparable roles.
Based on 240 similar postings.
Employer
About Apple Inc
Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software
Apple Inc currently has
3497 open roles
on FindRole.
Listed pay typically runs
$174,149–$277,600
across 2702 roles with salary data.
JOB TITLE: Senior Data Scientist - Experimentation
The Senior Data Scientist - Experimentation joins the Ads Experimentation team to develop and support a state-of-the-art experimentation platform for the Ads Platform organization. This role involves designing and building a new generation of tools to enable the safe, data-driven launch of features while maintaining privacy commitments. Key responsibilities include performing rigorous end-to-end analyses, designing statistical methods for marketplace dynamics, and leading the development of scalable data pipelines. The candidate will utilize SQL, Python, Pyspark, and Scala to build data products, dashboards, and monitoring systems. Core competencies include causal inference, A/B testing infrastructure, and observational techniques like regression, propensity score matching, and Diff in Diff. The work focuses on measuring treatment effects and advertiser value within a complex marketplace environment.
What does a Data Scientist earn in New York?
Median $173200 from 44 postings across 18 companies.
Design and build a new generation of experimentation platform for the Ads Platform organization.
Apply causal machine learning tools and statistical methods to estimate the incremental impact of interventions.
Design experiments that account for marketplace dynamics to yield reliable treatment effects.
Build and maintain scalable data pipelines with robust quality checks and monitoring systems.
Conduct end-to-end analyses using SQL, Python, and Pyspark to automate experiment reporting at scale.
Provide technical guidance to engineers and scientists on statistical techniques and experiment design.
Identify and prioritize high-impact questions by working directly with senior stakeholders.
Mentor junior engineers and scientists on the team.
What we're looking for
5+ years of experience in software and data science or statistics with an in-depth understanding of SQL and causal inference.
Experience in the Software Development Life Cycle (SDLC) is preferred.
Proficiency in SQL and Pyspark or Scala to conduct analyses and build data products like pipelines and dashboards.
Experience with A/B testing infrastructure and methodologies and deep understanding of randomized control trial assumptions.
Familiarity with causal machine learning tools and observational causal techniques like regression, propensity score matching, Diff in Diff, and instrumental variables.
Ability to design and analyze controlled experiments or counterfactual causal inference studies to estimate incremental and long-term impacts.
Experience in marketplace experimentation is a bonus.
Advanced Degree in Computer Science, Statistics, Applied Math or related field (preferred).
6+ years of industry experience building scalable applications (preferred).
Media Mix Modeling
Multi Touch Attribution
SQL
Python
R
Databricks
BigQuery
Machine Learning
Multivariate Regression
Optimization Algorithms
Generative AI
RShiny
Ads Data Hub
Data Science
Machine Learning
Python
R
SQL
Statistical Analysis
Data Pipelines
Feature Engineering
Causal Inference
Experimentation Frameworks
Model Monitoring
Responsible AI
Data Quality
Data Science
Optimization