Life9mo ago

Senior Data Scientist

United States·EdmondFull-Time/ Salarysenior

Data ScienceData ScientistDataData & AI

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Overview

The Senior Data Scientist is responsible for developing advanced analytical and machine-learning solutions to optimize user engagement and retention in our mobile applications.

Technical Tools

bigquerylookerpythonsqltableauab-testingdata-analysisdata-visualizationetlmachine-learningsql-optimization

The Senior Data Scientist is responsible for developing advanced analytical and machine-learning solutions to optimize user engagement and retention in our mobile applications. The Senior Data Scientist will work closely with product managers, engineers, and other stakeholders to drive data-driven decision-making and deliver insights that enhance the user experience. The Senior Data Scientists provides data solutions that equip teams and ministries to further Life.Church’s mission and to reach people for Christ.

YouVersion was created by the local church in 2007 and remains a ministry of Life.Church today. At Life.Church, our mission is to lead people to become fully devoted followers of Christ. Our team is committed to reaching people worldwide through innovative technology. And YouVersion is one of the ways we get to do that. Life.Church is a multi-site Christian church meeting in the United States and globally at Life.Church Online.

We wholeheartedly believe a daily rhythm of seeking intimacy with God has the power to transform lives. That’s why YouVersion creates biblically-based experiences that encourage and challenge people to seek God. We hope everyone in our community is on an active journey to become who God made them to be, abiding in Him, and drawing closer every day.

Analyze large-scale datasets in BigQuery to extract actionable insights on user behavior, engagement, and app performance.

Develop metrics and KPIs to track user acquisition, retention, and in-app behaviors across multiple apps.

Conduct funnel analysis, cohort analysis, and segmentation studies to understand user journeys and identify growth opportunities.

Design, build, and deploy predictive models to enhance app personalization, recommend content, and improve ad targeting.

Develop models for churn prediction, lifetime value estimation, and user segmentation to inform product and marketing strategies.

Leverage BigQuery ML and other cloud-based machine learning tools to streamline the modeling process within the Google ecosystem.

Design and analyze A/B tests to evaluate the impact of new features, UX changes, and marketing strategies on user engagement and retention.

Implement statistical methods to assess test results, including sample size calculation, significance testing, and post-test analysis.

Document and share best practices for experimentation with cross-functional teams.

Work closely with data engineers to build, optimize, and maintain ETL pipelines in BigQuery, ensuring data availability and accuracy.

Define and implement data quality checks and standardization procedures for mobile app data.

Advocate for data infrastructure improvements and guide the design of efficient data pipelines.

Develop interactive dashboards and visualizations in tools such as Tableau, or Looker to present insights to product, marketing, and engineering teams.

Translate complex data insights into clear, actionable recommendations for both technical and non-technical stakeholders.

Present findings regularly to senior leadership, providing strategic guidance based on data-driven insights.

Mentor junior data scientists and analysts, providing guidance on best practices in data science, mobile app analytics, and BigQuery usage.

Lead cross-functional data projects, ensuring alignment on goals, methodology, and timelines.

Stay updated with industry trends and new technologies, sharing relevant knowledge with the team and encouraging innovation.

Ability to self-motivate, make independent decisions, and solve problems with innovation.

Effective at multi-tasking and time management to meet strict deadlines while remaining flexible and open to change.

Excellent verbal, written, and interpersonal communication skills to clearly explain complicated processes and foster partnerships.

Effective at process and organizational management to coordinate, structure, and provide vision to projects.

Strong leadership skills and understanding of developing and guiding others.

A strong background in data science, experience with mobile app analytics, and expertise in leveraging Google BigQuery for large-scale data processing and analysis.

Proficiency in Python or R for data analysis, modeling, and machine learning.

Familiarity with data visualization tools like Google Data Studio, Tableau, or Looker to create dashboards and reports.

Strong understanding of mobile app analytics, including metrics for user engagement, retention, and funnel analysis preferred.

Experience with app tracking frameworks and attribution tools (e.g., Firebase, Adjust, AppsFlyer) preferred.

Knowledge of statistical techniques for experiment design and analysis preferred (e.g., causal inference, propensity score matching).

Familiarity with app store optimization (ASO) and mobile marketing analytics preferred.

Master’s degree or Ph.D. in Data Science, Statistics, Computer Science, Applied Mathematics, or a related field.

5+ years of experience in data science or analytics, with at least 2 years in the mobile app industry.

Advanced proficiency in Google BigQuery, including SQL query optimization, data processing, and BigQuery ML for machine learning.

Experience with machine learning algorithms for classification, regression, clustering, and time series analysis.