Overview Position Summary: This individual contributor position is responsible for supporting analytical projects on identifying business opportunities, answering business questions and developing business solutions. The team member will need to be able to understand business needs and create research and implementation plans using data, statistical models and machine learning techniques. The team member needs to have strong data and programming skills and be able to work closely with cross-functional teams of software engineers, data analysts and product leaders on business initiatives. Geo-Salary Information An in-person interview may be required during the hiring process State specific pay scales for this role are as follows: $94,458 to $179,048 (CA, NJ, NY, WA, HI, AK, MD, CT, RI, MA) $85,871 to $162,771 (NV, OR, AZ, CO, WY, TX, ND, MN, MO, IL, WI, FL, GA, MI, OH, VA, PA, DE, VT, NH, ME) $77,283 to $146,494 (UT, ID, MT, NM, SD, NE, KS, OK, IA, AR, LA, MS, AL, TN, KY, IN, SC, NC, WV) The expected base salary for this position will vary depending on a number of factors, including relevant experience, skills and location. Responsibilities Essential Job Functions: - The team member will work with various business departments to include UW, Claims, Marketing, and Advertising with understanding of business processes and business needs in these areas. - Identify the right business sources related to the issues and opportunities, conduct project work as assigned and performs ad-hoc analyses using statistical and machine learning algorithms to help improve business processes and decision-making. - Works independently with guidance and direction from advanced level data scientists and management. - Participates in discussions with colleagues regarding analysis needs. Reviews and discusses analyses with colleagues and managers as necessary. - Provide data support on projects and work closely with business on implementation through either analytical process or IT process. - Create monitoring procedures and reports for projects implemented, and identify potential opportunities to improve accuracy and efficiency. - Understand data sources from different applications and data infrastructure. Retrieves large amount of structured or unstructured data from various sources and apply advanced data manipulation techniques to prepare data for analysis. - Reviews data for accuracy and optimizes methods of data retrieval when necessary. Create, maintain and improve dynamic reports, graphs and charts through dashboard and other and programming and MS Excel. - Create procedures to streamline analysis procedures. - Establish automated procedures to help reduce cost and improve efficiency. - Answer questions and conduct ad hoc analysis from business on related reports. - Communicates proactively, clear and consistently with SMEs, EBI, IT, and Management in the various functional areas in order to understand each job function. Through this communication, the employee will be expected to increase the breadth of his/her understanding of the processes associated with these functions, and of the various KPI’s that drive business results in each area and overall. - Creates presentations breaking down problems identified, potential solutions. - Actively participates in meetings with to present findings and recommendations. Team member should have a strong background in creating and explaining meaningful graphs and be skilled at assembling and presenting PowerPoint presentations. - Regular attendance at work on a full-time schedule of at least 8 hours and 40 hours per week - Other functions may be assigned Qualifications Education: - Worker characteristics are normally acquired through the successful completion of a Bachelor’s degree in math, statistics, computer science or other related areas. Master’s Degree (or ACAS/FCAS) preferred. Experience: - At least 2 years of experience in data mining and data/statistical analysis. - At least 2 years experience with SQL and statistical software packages (Python, R, SAS) required. - At least 1 year experience working as a data scientist or similar role, with proven track record in data processing, predictive modeling, and machine learning techniques - At least 1 year of experience in insurance or financial service related fields Knowledge and Skills: - Demonstrated solid skills in data mining, machine learning, programming and optimization. - Knowledge with cloud-based advanced data and analytics environment. - Passion for problem-solving, comfort with ambiguity. - Ability to think conceptually, analytically and creatively. - Experience using R, Python and other programing languages. - Strong data skills and the ability to work with large structured and unstructured data sources. - Experience in of predictive modeling, general model building, and validation procedures. - Excellent problem-solving skills required. - Excellent analytical and critical thinking required. - Excellent written and verbal communication skills required. - Demonstrate Company’s Core Values. About the Company Why choose a career at Mercury? At Mercury, we have been guided by our purpose to help people reduce risk and overcome unexpected events for more than 60 years. We are one team with a common goal to help others. Everyone needs insurance and we can’t imagine a world without it. Our team will encourage you to grow, make time to have fun, and work together to make great things happen. We embrace the strengths and values of each team member. We believe in having diverse perspectives where everyone is included, to serve customers from all walks of life. We care about our people, and we mean it. We reward our talented professionals with a competitive salary, bonus potential, and a variety of benefits to help our team members reach their health, retirement, and professional goals. Learn more about us here: https://www.mercuryinsurance.com/about/careers Perks and Benefits We offer many great benefits, including: - Competitive compensation - Flexibility to work from anywhere in the United States for most positions - Paid time off (vacation time, sick time, 9 paid Company holidays, volunteer hours) - Incentive bonus programs (potential for holiday bonus, referral bonus, and performance-based bonus) - Medical, dental, vision, life, and pet insurance - 401 (k) retirement savings plan with company match - Engaging work environment - Promotional opportunities - Education assistance - Professional and personal development opportunities - Company recognition program - Health and wellbeing resources, including free mental wellbeing therapy/coaching sessions, child and eldercare resources, and more Mercury Insurance is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by federal, state, or local law. Pay Range USD $101,167.00 - USD $204,439.00 /Yr.

The Principal Biostatistician II functions independently as a statistical consultant/project manager by applying statistical, programming, and related methods such as machine learning and scientific expertise to the design, implementation, analysis, interpretation, and reporting of research, clinical and administrative studies. The Principal Biostatistician II must possess advanced level expertise in a wide variety of statistical techniques and other skills listed for Biostatistician, to meet the demands of study teams and investigators. The Principal Biostatistician II must possess advanced knowledge of biology and medicine and be able to identify and apply analytical approaches as they relate to these fields. The Principal Biostatistician II will direct development of case report forms (CRFs) and/or databases as well as monitor the progress for most biostatistical aspects of research and clinical studies. The Principal Biostatistician II manages and monitors all aspects of time and project management relating to staff effort, regulatory milestones, and/or goal timelines for at least one team of others either internal or external to the Department or Mayo Clinic. The Principal Biostatistician II will delegate tasks to statistical programmers, Biostatisticians, and other study personnel for most studies. The Principal Biostatistician II will summarize and communicate project findings to study team members, investigators, journal and grant reviewers, committees, and other individuals and entities as needed. The Principal Biostatistician II acts as an expert in writing statistical analysis plans and analysis data set specifications. The Principal Biostatistician II will contribute significantly to grant and report writing, scientific publications and/or regulatory reports, and may publish as a first or senior author in peer-reviewed journals. The Principal Biostatistician II functions as the primary statistician on most studies. The Principal Biostatistician II may serve as a co-investigator, key-personnel, or lead statistician independently on clinical trials, external collaborations or grants as approved by the Department. The Principal Biostatistician II has leadership role(s) in committees, task forces, or working groups within and/or outside of the Department or Mayo Clinic and may present in professional meetings outside of the Department or Mayo Clinic. Why Mayo Clinic Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans – to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic. Benefits Highlights - Medical: Multiple plan options. - Dental: Delta Dental or reimbursement account for flexible coverage. - Vision: Affordable plan with national network. - Pre-Tax Savings: HSA and FSAs for eligible expenses. - Retirement: Competitive retirement package to secure your future. Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is. Equal Opportunity All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the "EOE is the Law". Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization.

Job Description: Strategic Imperative: The Data Scientist role with a focus on Predictive Modeling, is responsible for developing, evaluating, and refining analytical and machine learning models that predict user behavior and optimize business outcomes across our suite of products. This role focuses on modeling, feature development, and offline evaluation to support performance marketing, insights and other strategic initiatives. The position applies statistical and machine learning techniques to large-scale behavioral and transactional data to improve ranking, recommendation and yield optimization. While this role partners closely with Engineering and ML Engineering teams, it does not own production deployment, infrastructure, or MLOps. Prodege: A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Great Hill Partners in Q4 2021 and strategic acquisitions of Pollfish, BitBurst & AdGate Media in 2022, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences. As an organization, we go the extra mile to “Create Rewarding Moments” every day for our partners, consumers, and team. Come join us today! *** We are seeking candidates who reside in the continental US. Work Visa sponsorship is available for qualified candidates. *** Primary Objectives: - Improve Yield Through Predictive Modeling: Drive yield optimization through the ideation and development of machine learning models for recommendations, ranking and yield optimization use cases - Organizational Data Science Advancement: Expand the application of machine learning across business functions through identification of opportunities and modeling, analysis, and offline evaluation. - Data Design: Leading feature engineering and defining key concepts to be formalized within the feature store. Qualifications - To perform this job successfully, an individual must be able to perform each job duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Detailed Job Duties: (typical monthly, weekly, daily tasks which support the primary objectives) - Business Translation & Modeling Framework Design: - Partner with Product and other business stakeholders to frame business problems into well-defined modeling objectives and hypotheses. - Select appropriate modeling techniques (e.g., classification, regression, deep learning, reinforcement learning) based on use case and data characteristics. - Define success metrics and evaluation criteria that align model performance with business impact. - Document modeling assumptions, tradeoffs, and intended use to ensure clarity, transparency, and alignment across teams - Data Analysis & Feature Development - Perform analysis on large-scale behavioral and transactional datasets to identify patterns, drivers, and potential predictive signal - Engineer features from user behavior, lifecycle activity, offer attributes, and revenue data to support modeling objectives - Collaborate with ML team to ensure features properly registered within feature store - Model Development & ML Collaboration: - Leverage appropriate modeling frameworks and packages to build high performing predictive models - Perform model tuning, validation, and comparison using appropriate metrics, cross-validation, and offline testing frameworks - Interpret model outputs to assess business relevance, identify strengths and limitations, and validate against observed behavior - Leverage appropriate frequentist and Bayesian approaches to measure model performance and define strategies for balancing exploration and exploitation - Document modeling approaches, performance results, and learnings in model cards to support reuse, iteration, and long-term knowledge building - Enable ML team to deploy models; collaborate on retraining and maintenance plans What does SUCCESS look like? Success in this role is demonstrated by the delivery of predictive models that materially improve yield management and optimizes engagement and revenue. Over time, success is reflected in models that are trusted by stakeholders, features that consistently capture meaningful behavioral signals, and clear evidence that model-driven decisions outperform prior approaches. Strong collaboration with Analytics Engineering and Machine Learning partners, thorough documentation of methods and learnings, and measurable business impact are hallmarks of high performance in this role. The MUST Haves: (ex: job cannot be done without these skills, education, experience, certifications, licenses) - Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field - Three or more (3+) years experience performing deep data analysis and training machine learning models - Strong foundation in machine learning and statistical modeling (classification, regression, ranking, optimization) - Experience with ranking, recommendation systems, and personalization models - Fluency in Python and common ML libraries (scikit-learn, XGBoost/LightGBM, PyTorch, or TensorFlow) - Fluency in SQL and ability to work with large, event-level datasets in data warehouse environments (e.g., Snowflake, BigQuery, Redshift) - Experience with feature engineering, model evaluation, and performance diagnostics - Strong analytical reasoning and ability to translate business questions into modeling approaches - Ability to apply AI and machine learning tools responsibly in support of predictive modeling, analysis, experimentation, and solution development, including validating outputs, documenting assumptions, and adhering to company security and confidentiality standards. - Clear communication skills, particularly in explaining model results and tradeoffs to non-technical stakeholders - Understanding of ML Ops concepts and the ability to collaborate effectively with ML Engineering and ML Ops teams.  - Excellent attention to detail. - Proficiency in critical thinking and problem solving. The Nice to Haves: (preferred additional skills, education, experience, certifications, licenses) - Hands-on experience managing ML deployments and designing feature stores and registries - Experience with AI/ML frameworks such as LangChain, LLMs, and HuggingFace - Worked with distributed data processing frameworks (Spark, Ray, Flink, Trino). - Experience with ML experiment tracking (e.g., ML Flow) - Experience in loyalty programs or performance marketing or market research - Experience with contextual multi armed bandit algorithms or reinforcement learning - Preference modeling methods used in Conjoint/MaxDiff - Understanding of Bayesian statistics inference (e.g., PyMC) Pay Transparency: The anticipated base salary range for this position is $150,000 to $180,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to; the type and length of experience within the job, type and length of experience within the industry, the type and length of knowledge and skills for the position, education, training, etc. Prodege is a multi-state employer and final compensation within this range could be impacted by work location. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Prodege Benefits: Prodege offers a comprehensive benefits package to US Full-time employees including medical, dental, vision, STD, LTD and basic life insurance. Employees receive flexible PTO, as well as paid sick leave prorated based on hire date. US Employees have eight paid holidays throughout the calendar year. Employees receive an option to purchase shares of Company stock commensurate with their position, which vests over four years. Equal Employment Opportunity Statement At Prodege, we are committed to creating a diverse and inclusive environment. We are proud to be an Equal Opportunity Employer and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by law. We encourage individuals of all backgrounds to apply. FCIHO Employers will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of FCIHO.

Job Description: Strategic Imperative: The Data Scientist, Applied Analytics is responsible for driving insights to drive decision-making across the business through rigorous analysis, experimentation, and business-focused data science. This role applies statistical methods, behavioral analysis, and data visualization to understand user behavior, optimize lifecycle marketing, evaluate product and monetization strategies, and inform how offers, incentives, and experiences are designed. Key interactions will occur with business and product stakeholders, informing business prioritization decisions. This position is centered on hands-on analytics, experimentation, and business impact. While the role may involve building analytical or predictive models as a means for key analysis, this role is not focused on live production models or ML Ops. Prodege: A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Great Hill Partners in Q4 2021 and strategic acquisitions of Pollfish, BitBurst & AdGate Media in 2022, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences. As an organization, we go the extra mile to “Create Rewarding Moments” every day for our partners, consumers, and team. Come join us today! *** We are seeking candidates who reside in the continental US. Work Visa sponsorship is available for qualified candidates. *** Primary Objectives: - Data Analysis & Insights Development: Drive data-informed progress across priority business areas by delivering rigorous analysis, actionable insights, and close partnership on optimization initiatives. - User Intelligence, Segmentation & Marketing Enablement: Develop and operationalize user-level insights, segmentation frameworks, and behavioral analysis that enable smarter targeting, personalization, and lifecycle engagement across growth and marketing programs. - Experimentation, Learning & Strategic Insight: Enable confident decision-making through statistically sound experimentation, structured insight generation, and systematic documentation of learnings to inform business planning, long-term strategy, and continuous improvement. Qualifications - To perform this job successfully, an individual must be able to perform each job duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Detailed Job Duties: (typical monthly, weekly, daily tasks which support the primary objectives) - Analytical Insights & Decision Support: - Aid executive decision making by answering key questions about user behavior. - Enable marketing decisions by conducting rigorous analyses of user acquisition, activation, and lifecycle performance to identify drivers and opportunities. - Translate complex datasets into clear, actionable insights that inform product, marketing, and revenue strategy. - Partner with cross-functional stakeholders to evaluate initiatives, diagnose performance issues, identify optimization opportunities, and build optimization frameworks. - Communicate findings through compelling narratives and visualizations that support confident, data-driven decisions. - Document learnings and provide a clear understanding of underlying business dynamics. - Prototype and discover early stage ML models as appropriate to support advancement of key business areas. - Experimentation & Measurement: - Design, analyze, and interpret A/B tests and controlled experiments to evaluate product features, marketing programs, incentives, and monetization strategies. - Establish best practices for experimental design, statistical validity, and result interpretation to ensure reliable decision-making. - Measure incremental impact, causal effects, and business outcomes across lifecycle stages including acquisition, activation, retention, and re-engagement. - Partner with Product, Growth, and Marketing teams to define hypotheses, success metrics, and post-test actions. - Document experimental results and key learnings in a centralized knowledge base to promote reuse, transparency, and continuous improvement. - Data Semantics & Feature Enablement - Collaborate with BI team by informing data requirements for the semantic layer. - Expose behavioral learnings to Data Scientists & ML team to inform feature development. What does SUCCESS look like? Success in this role is demonstrated by consistently translating data into clear, actionable decisions that improve product performance, lifecycle marketing effectiveness, and monetization outcomes. This is reflected in well-designed experiments and frameworks that drive confident business choices, analytical insights that meaningfully influence strategy, and strong partnerships with Analytics Engineering and Machine Learning through precise data definitions and feature guidance. Over time, success is evident in a growing body of documented learnings, trusted metrics, and a measurable impact on how the organization tests, learns, and optimizes. The MUST Haves: (ex: job cannot be done without these skills, education, experience, certifications, licenses) - Bachelor’s or Master’s degree in Statistics, Economics, Data Science, Mathematics, or a related quantitative field. - Three or more (3+) years experience in applied analytics roles. - Strong foundation in statistical analysis and experimental design, including hypothesis testing and causal reasoning. - Understanding of frequentist and Bayesian statistical inference (e.g., PyMC) and demonstrated experience with A/B testing and experimentation frameworks. - Experience leading the analysis and optimization of lifecycle marketing performance across the user journey. - Fluency in SQL and ability to work with large, event-level datasets in data warehouse environments (e.g., Snowflake, BigQuery, Redshift). - Proficiency in Python/R (pandas, matplotlib/seaborn, tidyverse, or similar). - Ability to develop effective data visualizations that clearly communicate insights to business stakeholders. - Ability to apply AI and machine learning tools responsibly in support of predictive modeling, analysis, experimentation, and solution development, including validating outputs, documenting assumptions, and adhering to company security and confidentiality standards. - Strong communication skills with the ability to translate complex analysis into clear, actionable business insights. - High attention to data quality, metric definitions, and analytical rigor. The Nice to Haves: (preferred additional skills, education, experience, certifications, licenses) - Experience in loyalty programs or performance marketing or market research. - Advanced Python skills and familiarity with common ML packages. - Experience building interactive dashboards in modern BI platforms. - Experience with site and product analytics tools (e.g. Amplitude). Pay Transparency: The anticipated base salary range for this position is $150,000 to $180,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to; the type and length of experience within the job, type and length of experience within the industry, the type and length of knowledge and skills for the position, education, training, etc. Prodege is a multi-state employer and final compensation within this range could be impacted by work location. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Prodege Benefits: Prodege offers a comprehensive benefits package to US Full-time employees including medical, dental, vision, STD, LTD and basic life insurance. Employees receive flexible PTO, as well as paid sick leave prorated based on hire date. US Employees have eight paid holidays throughout the calendar year. Employees receive an option to purchase shares of Company stock commensurate with their position, which vests over four years. Equal Employment Opportunity Statement At Prodege, we are committed to creating a diverse and inclusive environment. We are proud to be an Equal Opportunity Employer and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by law. We encourage individuals of all backgrounds to apply. FCIHO Employers will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of FCIHO.