Senior Data Scientist

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LocaliQ

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

📣 Marketing

☁️ SaaS

🤝 B2B

Marketing • SaaS • B2B

LocaliQ is a digital marketing platform and services provider that helps businesses grow leads, revenue, and online visibility through data-backed, multi-channel marketing solutions. LocaliQ offers paid advertising (search, display, video, social), SEO, website and listings management, targeted email marketing, landing pages, AI-powered lead management (Dash), reporting and analytics, and managed local marketing expertise across many verticals and multi-location businesses. The company targets small-to-medium businesses and agencies with an all-in-one platform and professional services; site metrics indicate large scale: 283M leads generated, $15. 9B total revenue attributed, 142M hours saved, and 512K+ businesses served.

📋 Description

• Partner with Product Managers, Engineers, and cross-functional stakeholders to answer strategic product questions through reporting, analysis, deep dives, and predictive or prescriptive modeling • Forecast business outcomes and identify opportunities to improve product performance • Define, maintain, and improve key product metrics, dashboards, and monitoring frameworks • Apply machine learning techniques to customer behavior, engagement, retention, churn, propensity scoring, segmentation, recommendation systems, and personalization initiatives • Evaluate product launches, feature changes, and AI-enabled initiatives against success metrics and communicate recommendations • Support experimentation and measurement design, including hypothesis development, test readouts, and post-launch evaluations • Build scalable modeling, reporting, and self-service analytics assets • Partner with data engineering and platform teams to improve data quality, instrumentation, metric definitions, and reporting pipeline reliability • Translate complex findings into concise narratives, presentations, and recommendations • Support AI data initiatives by helping build and evaluate models, measure features, and assess customer and business impact

🎯 Requirements

• Bachelor's degree in a quantitative field such as Statistics, Economics, Mathematics, Computer Science, Engineering, or a related discipline • 5+ years of experience in data science, product analytics, decision science, or a closely related analytics role supporting product teams • Strong SQL skills • Proficiency in Python for data analysis, statistical modeling, predictive modeling, and data exploration • Experience with PyTorch, scikit-learn, and other machine learning frameworks • Familiarity with feature engineering, model selection, cross-validation, hyperparameter tuning, and performance evaluation • Experience developing dashboards and visualizations for executive reporting and product decisions • Strong understanding of product metrics, experimentation, hypothesis testing, and statistical analysis • Experience working with large, messy, and multi-source datasets • Excellent communication skills and ability to explain technical findings in plain language • Experience supporting AI or ML-related product initiatives, model evaluations, or measurement frameworks is preferred • Advanced degree is preferred • Experience in media, ad tech, mar tech, digital subscriptions, marketplaces, or other product-led businesses • Experience in cloud data environments and product instrumentation best practices • Experience in highly cross-functional environments with shifting priorities

🏖️ Benefits

• Annualized base salary of $115,000–$120,000 • Variable compensation may be applicable • Remote work