Data Science- WFH

# DATA SCIENCE LEAD ## About the Role Prove is seeking a Data Science Lead within its Business Operations team to serve as a strategic architect and research leader for the organization’s data ecosystem. This role focuses on scalable data architecture, research and development of novel data sources, rigorous analytical methodologies, and the integration of high-quality data into downstream production solutions. The Data Science Lead will bridge research and production by evaluating emerging data sources and technologies, establishing analytical standards, overseeing data integration, and translating complex technical architectures into strategic business value. This is a US Remote position reporting to the Director, Data Science. ## Key Responsibilities Design and oversee scalable data architectures supporting advanced analytics, machine learning modeling, and real-time processing. Research, evaluate, and pressure-test internal, external, and alternative data sources, including synthetic data, IoT streams, and third-party APIs. Lead ideation and feature engineering for new data sources and document their alignment with current and future data architecture. Lead rapid prototyping and proof-of-concept initiatives to validate new technologies, algorithms, and data structures before production scaling. Technically assess data vendors and partners for data quality, density, and integration capabilities. Define and document standard methodologies for statistical analysis, experimental design, including A/B testing, and machine learning modeling. Establish validation protocols and evaluation metrics such as precision/recall, drift detection, and bias/fairness audits. Monitor and improve data and model integrity through rigorous analytical practices. Translate academic research and emerging industry trends into practical business methodologies. Bridge R&D and production by supporting the integration of analytical models and data sources into core business products and solutions. Oversee data delivery contracts between the data science ecosystem and downstream software applications. Support the creation of clean, well-documented APIs for data delivery and integration. Develop strategic data science infrastructure and architecture roadmaps aligned with corporate scaling goals. ## Key Deliverables Data Source Playbook: Framework for scoring, vetting, and onboarding new data assets. Methodology Registry: Centralized repository of approved statistical models, evaluation metrics, and ingestion protocols. Feature Importance Registry & Feature Engineering Roadmap: Repository connecting current data sources to product value and impact, including potential substitutes and opportunities to leverage signals in new and differentiated ways. Architectural Roadmap: 12-month to 3-year vision aligning data science infrastructure with corporate scaling goals. ## Required Qualifications 6+ years of experience in Data Science and/or Data Engineering. At least 2 years of experience in a technical leadership or architectural role. Proficiency in Python, R, and SQL. Experience with cloud platforms such as AWS, GCP, or Azure. Experience with big data technologies such as Spark and Kafka. Experience with orchestration tools such as Airflow. Experience with MLOps tools. Deep understanding of data modeling and schema design, including SQL and NoSQL. Strong knowledge of statistical evaluation and MLOps deployment patterns. Experience in R&D functions that bridge research with production. Ability to translate complex technical architectures into strategic business value for non-technical stakeholders. ## Preferred Qualifications No additional qualifications are explicitly identified as preferred in the source job description. ## Skills & Competencies Data science Data engineering Data architecture Scalable data architecture Machine learning Statistical analysis Experimental design A/B testing Data modeling SQL/NoSQL schema design Python R SQL AWS GCP Azure Spark Kafka Airflow MLOps Feature engineering Data source evaluation Proof-of-concept development API and interface design Data integration Model validation Precision/recall evaluation Drift detection Bias and fairness audits Technical leadership Strategic communication ## Education & Experience Education No specific degree requirement is stated in the source job description. Experience 6+ years in Data Science and/or Data Engineering. 2+ years in a technical leadership or architectural role. Experience bridging research and production through R&D, data architecture, analytical methodologies, and MLOps deployment. ## Work Arrangement & Schedule Location: US Remote Work Arrangement: Remote Department: Business Operations Reports To: Director, Data Science FLSA Status: Exempt Work Authorization: This role is not eligible for work authorization sponsorship. Schedule: Flexible hours are listed among company benefits. ## Compensation & Benefits Anticipated Salary Range: $179,000–$200,000 plus variable commission/company bonus. Offered salary is determined based on factors including education, experience, knowledge, skills, geographic location, abilities, internal equity, and market data. Prove follows a geographic, market-driven compensation philosophy. Equity Plan. Modern Health financial, mental, and physical wellness support. 401(k) retirement plan and match for US offices. Unlimited vacation and flexible hours. Comprehensive medical benefits for employees and families. Emotional and physical wellness services, including EAP and Prove Well-Being Reimbursement. Office-specific snacks and beverages at certain locations. Daily GrubHub lunch stipend when coming into the office at US offices. Additional company programs and workplace benefits. ## Compliance / Additional Information Prove states that it is an equal opportunity employer committed to providing equal employment opportunity regardless of race, color, religion, gender or sexual orientation, age, marital status, national origin, citizenship status, disability, veteran status, or other personal characteristics. The position description may be adjusted based on the successful candidate’s capabilities and changing business conditions. Additional related duties may be assigned by the supervisor. Prove encourages candidates to apply even if their experience does not align perfectly with every listed qualification.

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