Senior Data Scientist, Forecasting and Analytics

Location: Hybrid role based in Frisco/Dallas, TX, New York, NY, San Jose, CA, or Newport Beach, CA; office attendance is required as needed, with the remainder worked from a home office.

Salary: USD $107,430–$176,490 per year, depending on experience and qualifications.

Company

hirify.global develops personal security solutions that protect consumers, families, and communities in an always-connected world.

What you will do

• Own and maintain forecasting models for revenue, demand, conversion, retention, and customer value.
• Translate historical trends, seasonality, campaign activity, customer behavior, macro factors, and business assumptions into forecasts, scenarios, and planning tools.
• Monitor forecast accuracy, diagnose variance against plan, and recommend adjustments based on changing business conditions.
• Develop machine learning and advanced analytics models for segmentation, propensity, churn, retention, personalization, and lifetime value.
• Partner with Marketing, Finance, Product, Analytics, and Data Engineering to define analytical approaches, data requirements, and success metrics.
• Present clear, executive-ready insights through dashboards, presentations, and business readouts.

Requirements

• 7+ years of experience applying data science, machine learning, forecasting, or advanced analytics in a business environment.
• Strong proficiency in Python, SQL, and common data science or statistical modeling libraries.
• Strong knowledge of time-series analysis, forecasting, seasonality, trend, lag effects, scenario planning, and model backtesting.
• Experience with marketing or customer analytics, campaign performance, acquisition, retention, conversion, or lifetime value analysis.
• Ability to structure ambiguous business questions into analytical plans and actionable recommendations.
• Strong communication and data storytelling skills for influencing marketing and business stakeholders.

Nice to have

• Master’s degree or PhD in a quantitative discipline.
• Experience with customer lifecycle, journey, subscription, ecommerce, SaaS, or consumer digital analytics.
• Familiarity with experimentation, causal inference, uplift modeling, survival analysis, Bayesian modeling, or personalization.
• Experience with large-scale customer, behavioral, clickstream, campaign, planning, or transaction-level datasets.
• Experience with Databricks, Snowflake, BigQuery, or similar cloud data platforms.

Culture & Benefits

• Flexible work hours and family-friendly employee benefits.
• Bonus program and 401(k) retirement plan.
• Medical, dental, vision, life, and disability coverage.
• Paid parental leave, paid company holidays, sick time, and vacation.
• Support for community involvement and a commitment to diversity and inclusion.