Senior Data Scientist, Audience Analytics for Healthy Communities

About Fors Marsh: Fors Marsh is a premier, internationally recognized quantitative research powerhouse, strategic communications innovator, and certified B Corporation operating on an absolute mission to study human behavior from all angles, unpack complex social contexts, and design data-driven solutions that influence decision-making and move global populations to positive, lasting action. Purpose-built to impact public health, shape resilient local communities, and support effective, accountable institutions, Fors Marsh operates at the forefront of behavioral science execution. Celebrated as a Top Workplace for seven consecutive years, our multi-disciplinary team partners hand-in-hand with leading federal agencies, national foundations, and public sector organizations to optimize massive public education platforms. Driven by a culture of curiosity, analytical rigor, and deep social contribution, the firm provides high-agency data scientists with an uncompromised remote canvas to leverage state-of-the-art predictive algorithms, manipulate massive cross-cutting consumer matrices, and deploy interactive visualization systems safely across the United States.

Position Overview

We are seeking a highly analytical, systems-minded, and context-driven Senior Data Scientist to join our core centralized Audience Analytics for Healthy Communities (AA4HC) division in a full-time remote capacity across the United States. Operating under the internal corporate career title of Senior Scientist I, you will step up to claim true individual strategic and operational accountability for running advanced quantitative research, data engineering, and predictive infrastructure optimization supporting high-stakes public health campaigns, explicitly including nationwide tobacco and nicotine education tracks. Shifting completely away from routine static data entry typing, monotone administrative spreadsheet sorting, or basic report copying, you will operate as a principal research architect—partnering face-to-face with federal agency directors, media distribution vendors, and internal communication strategists. This position requires an enterprise tech or public health research veteran with 5+ years of craft depth who maps out multi-tenant audience segmentations fluidly natively using Data Scientist statistical structures, constructs automated data-cleansing pipelines smoothly natively using Python Scripting languages, and commands complex machine-learning algorithms confidently under strict federal reporting deadlines.

Key Responsibilities

• Full-Lifecycle Behavioral Data Architecture: Own, design, and implement rigorous data architectures to identify, understand, and track targeted audience populations across national public education initiatives cleanly natively utilizing Data Scientist strategies.
• Automated ETL/ELT Pipeline Engineering: Formulate, write, and manage optimized cleaning scripts and process-review automation layers to ingest advertising analytics and longitudinal survey datasets cleanly natively leveraging Python Scripting and R within medallion storage frameworks.
• Advanced Predictive and Statistical Modeling: Conduct deep-dive data diagnostics, applying supervised, semi-supervised, and unsupervised machine-learning models—including generalized linear/additive models, random forests, mixed-effect structures, clustering techniques, and Bayesian approaches—to drive causal inference and audience segmentation.
• Enterprise Dashboard and Visualization Governance: Build, scale, and maintain interactive trend dashboards and data exploration layers across Tableau and PowerBI to streamline multi-channel media tracking and reporting.
• Cross-Functional Vendor Data Realignment: Coordinate directly with external media vendors, data syndicators, and internal campaign cells to securely integrate disparate advertising streaming data layers into core analytical systems.
• High-Signal Stakeholder Consultative Diplomacy: Lead regular client-facing presentations, technical status meetings, and milestone briefings before federal administrators to translate abstract quantitative findings into actionable media placement solutions.
• Cloud Technology and Infrastructure Execution: Query, extract, and manipulate large, nuanced datasets safely within cloud computing servers, configuring storage blocks and model containers natively inside AWS systems (S3, RDS, and SageMaker).
• Model Evaluation and Validation Hygiene: Enforce uncompromised statistical standards across all project deliverables, conducting cross-validation and rigorous model performance evaluations to guarantee data integrity.

Required Skills & Qualifications

• A minimum of 5 years of verified professional history running advanced data science operations, quantitative social science research, corporate audience segmentation modeling, database engineering, or technical analytics consulting.
• Mandatory Advanced Academic Background: Possession of a formal university Master’s degree in Data Science, Social Science, Public Health, Statistics, Marketing, or a closely related quantitative field of study (with an absolute professional preference for candidates holding a PhD).
• Expert-tier capability writing custom machine-learning scripts, optimizing data-processing loops, and constructing predictive models natively utilizing Data Scientist methodologies.
• Practical operational familiarity organizing medallion data layers, cleaning unstructured survey tracking tables, and configuring ETL filters natively using Python Scripting languages (paired with functional proficiency in R and SQL parameters).
• Demonstrated capability navigating large, highly complex, and nuanced datasets, balancing multiple cross-cutting analytical tasks independently within an agile project environment.
• Outstanding written, verbal, and visual data-presentation communication attributes in fluent English, enabling absolute confidence when defending analytical models or presenting strategic briefs before federal oversight boards.
• Government Security Profile: Applicants must remain willing and eligible to undergo a low-level government security investigation and meet criteria for access to sensitive public information.
• Location Context: Position open exclusively to qualified quantitative data scientists based permanently and resident within the borders of the United States to operate under a 100% remote work-from-home layout.

Preferred Strategic Indicators (Nice to Have)

• Prior commercial media engineering or research history operating explicitly inside or adjacent to commercial audience data panels (such as MRI-Simmons, Nielsen, or Claritas).
• Direct professional background collaborating with federal public health clusters (HHS, FDA, CDC, CMS) or prominent statistical agencies (Census Bureau, BLS, BEA).
• Hands-on technical familiarity mapping spatial and geographical insights using GIS software tools (such as ArcGIS platforms).
• An outcome-driven personal philosophy rooted in high statistical curiosity, an absolute aversion to brittle or ungrounded data models, and an intense passion for turning complex data science into life-saving community strategies.

What We Offer

• Vetted, Certified B-Corp Salaried Blueprint: A competitive full-time baseline annual corporate salary package calibrated precisely between $92,000 and $105,000 USD to evaluate your data science authority, framework craftsmanship, and federal campaign execution velocity, supplemented by corporate performance incentives.
• The exceptional professional canvas to claim a foundational data leadership seat, directly transforming data insights into nationwide health awareness initiatives.
• Profound work-from-home remote parameters offering a 100% remote virtual setting across America, complete scheduling trust, and zero physical geographic office commuting friction.
• Immediate baseline access to premium comprehensive group healthcare protections, providing **100% company-covered medical, dental, vision, and long/short-term disability plans for employees**.
• Access to elite financial accumulation frameworks, featuring generous company-matching retirement contributions with zero vesting periods starting your third month of employment.
• Generous lifestyle upscaling advantages, including a flexible personal time off tracking system to easily balance domestic commitments, a customizable floating holiday bank to celebrate personal values, paid corporate time off for volunteer projects, and curated staff-led affinity groups.
• Dedicated individual training and development budgets designed explicitly to finance external advanced technology courses, data science certifications, and technical library access to compound your hard skills.