Data Scientist

Position Overview

We are seeking an experienced Data Scientist for a full-time remote contract engagement starting immediately and lasting until December 18th. This approximately six-month role involves working closely with insights and analytics teams to harness predictive capabilities from brand, business, and media data to enhance marketing impact and overall business outcomes.

Key Responsibilities

• Design, manage, and assess synthetic data pilot projects, including evaluating their feasibility, methodologies, data quality, and practical implementations related to brand insights.
• Develop and advise on predictive models that unify brand health metrics, business performance indicators, and media spend data to establish data-driven targets and uncover critical correlations.
• Construct forecasting frameworks to anticipate the market success of creative initiatives by identifying leading indicators and signals predictive of performance.
• Handle complex datasets from diverse sources, undertaking data cleaning, structuring, and harmonization to support accurate modeling endeavors.
• Detect insightful patterns and relationships across brand, media, and business datasets beyond conventional reporting measures.
• Communicate analytical results and model interpretations clearly to non-technical stakeholders such as marketing, brand strategy, and finance teams, enabling actionable decision-making.
• Thoroughly document all methodologies, assumptions, and model processes to guarantee reproducibility and facilitate knowledge transfer to the internal team post-engagement.
• Collaborate effectively with insights and analytics teams to validate approaches, verify findings, and align on project priorities.

Qualifications

• Bachelor's degree in Mathematics, Statistics, or a related technical discipline, or equivalent experience.
• Over 8 years of professional experience in analytics, including proficiency with SQL for data querying, Python scripting, and/or statistical software like R.
• Extensive background in tackling analytical challenges utilizing quantitative methods, understanding ecosystems and user behavior, defining metrics, designing experiments, and leading data-focused projects through full lifecycle execution.
• Demonstrated capability in building and validating predictive models such as regression, time-series forecasting, causal inference, and machine learning techniques.
• Hands-on experience leveraging machine learning and statistical analyses for developing data-driven solutions and advanced methodological research.
• Preferred experience within technology sectors, ideally consumer-centric, data-rich organizations.
• Ability to work autonomously in a dynamic, fast-paced environment involving multiple stakeholders and shifting requirements.
• Strong communication skills enabling translation of complex modeling outcomes into compelling insights for senior-level, non-technical audiences.

Required Technical Skills

• Expertise in constructing and validating predictive models including regression, time-series, causal inference, and machine learning.
• Proficiency in applying machine learning and statistical methods to build analytical solutions and conduct research.
• Excellent communication skills for effectively conveying complex technical concepts to diverse audiences.

Preferred Skills and Experience

• Doctorate degree in quantitative fields such as Statistics, Computer Science, Economics, or Applied Mathematics is highly regarded.
• Knowledge and experience with synthetic data generation methods, including understanding their appropriate applications and constraints.
• Familiarity with marketing measurement techniques, media mix modeling, and brand analytics.
• Demonstrated skills in using AI tools to optimize and reengineer workflows, driving measurable enhancements in efficiency and quality.
• Experience applying responsible AI principles, including risk evaluation, bias mitigation, and quality control.
• Continuous development and mastery of AI-related skills such as prompt engineering and agent orchestration, with awareness of emergent AI technologies.