Title: Data Scientist, Finance Location: Los Angeles, CA Department: Engineering Job Description: Employment Type Full time Department EngineeringData & Marketplace Integrity Compensation - $194K – $215K • Offers Equity The salary or hourly rate range may be inclusive of several levels that would be applicable to the position. Final salary or hourly rate will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary or hourly rate, not benefits or equity. OverviewApplication Join the Future of Commerce with Whatnot! Whatnot is the largest livestream shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops. As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact. We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce. Role - Partner closely across the business to find improvements/opportunities and influence decisions using data analytics methodologies and tools. - Act as the data owner for Finance functions, including but not limited to accounting, tax, strategic finance, profitability, and the executive office. - Build production-quality data products, dashboards, notebooks, and actionable KPIs to convey critical financial insights. - Drive incremental improvements in contribution margin by deeply understanding business drivers and analyzing cross-functional initiatives. - Collaborate on data and analytics engineering work to ensure financial datasets are enriched, reliable, and scalable. You People who do well at Whatnot tend to be comfortable figuring things out as they go, biased toward action, and genuinely curious about what they're building. They care more about outcomes than credit and stay close to the product and the people using it. We are looking for intellectually curious, highly motivated individuals with a strong background in data tooling and visualization. The ideal candidate thrives at the intersection of finance and engineering, prioritizing speed and utility over complex statistical modeling. In addition to 6+ years of experience in the Data Analytics/Science field, you should have: - A background with some form of Consulting, Fintech, Payments, or Finance; essentially, finance should not be a new concept to you. - Expertise in data engineering and analytics engineering essentially, data storage and architecture should not be a new concept to you. - A strong background in data tooling and visualization, with a firm grasp of business intelligence tools and self-serving notebooks. Bonus points for D3, React or Web app development. - Expert-level SQL skills for data analysis, reporting, and dashboarding. - Bachelor’s degree in Computer Science, Finance, or a related technical field. - Excellent verbal communication skills, with the ability to articulate complex financial-data concepts to both technical and non-technical collaborators Benefits - Generous Holiday and Time off Policy - Health Insurance options including Medical, Dental, Vision - Work From Home Support - Home office setup allowance - Monthly allowance for cell phone and internet - Care benefits - Monthly allowance for wellness - Annual allowance towards Childcare - Lifetime benefit for family planning, such as adoption or fertility expenses - Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally - Monthly allowance to dogfood the app - All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!). - Parental Leave - 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence. 1212 EOE Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.

Lead and optimize bioprocess development for plasmid DNA and protein biologics, ensuring compliance with regulatory standards while driving technology innovation and coordinating technical transfers across cross-functional teams.

Title: Manager, Data Scientist - Eso Location: Pittsburgh United States Job Description: Category Laboratory Location Pittsburgh, Pennsylvania Job function Operations Job family Laboratory Operations Shift Day Employee type Regular Full-Time Work mode Remote Job Description Healthcare Analytics Solutions (HAS) is an innovative team within Quest Diagnostics that leverages Quest data to develop products and services to improve outcomes in healthcare across many different markets (Pharma, Clinical Trials, Health Plans/Payers, Hospitals/Health Systems, and Public Health agencies). Join HAS to build, productionize, and operationalize clinical ML products using billions of results from Quest laboratory data. You will partner with clinicians, engineers, and product teams to deliver robust, compliant, and well‑documented models that impact patient care and downstream products. Fully remote, minimal travel required; strong emphasis on hands‑on production experience and pragmatic problem solving. Responsibilities: - End-to-end ML delivery: data curation, feature design, modelling, validation, CI/CD deployment, and monitoring. - Productionization: containerization, model serving, performance tuning, rollout strategies, and observability (drift, performance, alerts). - Model governance: reproducibility, versioning, bias/fairness checks, and audit-ready documentation. - Integration of advanced analytics and machine learning models into business products and services including business intelligence dashboards and real-time analytics. - Curation of data sets from Quest and non-Quest data sources in support of deriving business insights driven by advanced analytics. - Cross-functional partnership with clinicians and product owners to define outcomes, acceptance criteria, and validation plans. - Mentor and raise engineering standards across the team: coding best practices, testing, and deployment patterns. - Translate technical results into clear explanations and recommendations for technical and executive stakeholders. Qualifications: - 5+ years demonstrated track record delivering ML models to production (architecture, deployment, and monitoring), preferably in the healthcare industry. - 5+ years relevant experience with Python and SQL; production-grade code and testing practices. - Practical experience with model serving and monitoring, CI/CD for ML, and feature pipeline orchestration. - Experience working with healthcare data (labs, EHR, claims) and familiarity with PHI handling/HIPAA considerations. - Strong statistics, model evaluation, and pragmatic approach to validation. - Excellent communication and problem‑solving skills; comfortable leading technical discussions with clinicians and engineers and presenting to senior executives - A bachelor's degree from an accredited college or university in a related area of Data Science, Statistics, Computer Science, Mathematics, Economics, or Information Technology. Master's or PhD preferred. Preferred - Familiarity with feature stores and SHAP/interpretability tooling. - Prior experience in regulated environments or deploying clinical decision support tools. - Demonstrated ability to leverage data visualization tools and software to present advanced analytics that are easy to interpret and spot patterns, trends, and correlations - Experience developing, deploying, and monitoring production models in the C3.ai platform - Excellent scientific writing skills; we may publish studies based on novel models or methods - Experience supporting the creation of SOWs and Contracts. - Aptitude in other programing languages like R, SAS, JavaScript 58948 Quest Diagnostics honors our service members and encourages veterans to apply. While we appreciate and value our staffing partners, we do not accept unsolicited resumes from agencies. Quest will not be responsible for paying agency fees for any individual as to whom an agency has sent an unsolicited resume. Equal Opportunity Employer: Race/Color/Sex/Sexual Orientation/Gender Identity/Religion/National Origin/Disability/Vets or any other legally protected status.

• Responsible for developing, implementing, and optimizing advanced analytics and machine learning models to support data-driven decision-making across the organization • Applies statistical analysis, predictive modeling, and data exploration techniques to solve business problems, generate insights, and improve performance across functions such as marketing, operations, and risk • Identifies and evaluates data sources and collaborates with BI engineers to automate data collection processes • Performs preprocessing, cleansing, and validation of structured and unstructured datasets • Analyzes complex datasets to identify trends, patterns, and actionable insights • Develops and presents data visualizations and reports to communicate findings to stakeholders • Proposes data-driven solutions and strategies to address business challenges • Collaborates with cross-functional teams including engineering, analytics, and product development • Develop, implement, and maintain statistical and machine learning models to address business challenges and improve decision-making • Ensures data integrity, accuracy, and consistency across analyses