• Partner with Product & Engineering teams to analyze and optimize product engagement and the full customer funnel, including acquisition, conversion, retention, and churn. • Build and maintain statistical models and analyses related to key product use cases such as A/B tests, cohort analysis, and conversion/retention optimization. • Design, analyze, and interpret experiments (A/B and multivariate tests) across marketing channels and on-site experiences, ensuring statistical rigor and clear recommendations. • Translate ambiguous business questions into well-scoped analytical projects with clear success metrics and timelines. • Collaborate with data engineering and analytics engineering partners to define data requirements and ensure reliable, well-modeled datasets for marketing analytics. • Clearly communicate findings and recommendations to non-technical stakeholders through presentations, dashboards, and written documentation. • Contribute to shared analytics and modeling best practices within the data science team, including code quality, validation, and documentation. • Support junior team members through informal mentorship, code review, and knowledge sharing where appropriate. • Stay current on industry trends and techniques in marketing analytics, experimentation, and applied data science, and apply them pragmatically to Hone’s context.

Role Description We’re seeking a Data Scientist with hands-on experience in machine learning engineering and MLOps. In this role, you’ll own the full model lifecycle — from research and experimentation through deployment, monitoring, and iteration. You’ll work within our AWS SageMaker Studio environment and collaborate closely with engineering, operations, and product teams to deliver models that drive measurable business outcomes. Key Responsibilities - Develop, train, and evaluate machine learning models to solve business problems across operations, legal services, and marketing. - Own the full ML lifecycle: data preparation, feature engineering, model training, validation, deployment, and monitoring. - Build and maintain MLOps pipelines using AWS SageMaker Studio, including experiment tracking, model registry, and automated retraining workflows. - Partner with product and operations teams to translate business requirements into data science solutions. - Monitor deployed models in production, identify performance degradation, and drive continuous improvement. - Document methodologies, model performance benchmarks, and technical decisions for internal knowledge sharing. - Stay current with advances in ML and data science tooling, and advocate for best practices across the team. Qualifications - 3+ years of experience in data science or a closely related role, with demonstrated ML engineering and MLOps responsibilities. - Strong proficiency in Python for data science and ML development (pandas, scikit-learn, PyTorch or TensorFlow). - Hands-on experience with AWS SageMaker Studio for model development, training, and deployment. - Solid understanding of MLOps principles: model versioning, pipeline automation, drift detection, and production monitoring. - Experience with SQL and working with structured data in cloud data warehouses or relational databases. - Proven ability to translate complex data science findings into clear, actionable insights for non-technical stakeholders. - Strong self-direction and communication skills suited for a remote work environment. Requirements - Experience in the legal, collections, or financial services industry. - Background in targeted mail marketing, direct mail modeling, or customer segmentation. - Familiarity with AI coding agents and agentic development workflows (e.g., Claude, Copilot, Cursor, or similar tools). - Experience with propensity modeling, uplift modeling, or response prediction. - Exposure to LLM-based workflows or applied NLP in a production setting. - Data engineering experience with modern tooling such as Dagster, Airbyte, and dbt. - Familiarity with AWS data services including Glue, Lambda, Redshift, and Step Functions. Benefits - Fully remote position with flexible working hours. - Comprehensive health, dental, and vision insurance. - 401(k) with company match. - Paid time off and company holidays. - Opportunity to shape data science strategy at a growing, industry-leading company. Salary Range $110,000-$130,000 depending on experience.

• Develop descriptive and predictive data science solutions focused on process optimization, resource allocation, and decision support for the portfolio’s health and performance areas. • Create sales performance indicators for products and build solutions that increase the portfolio’s profitability. • Execute all stages of the data science solution lifecycle: business understanding, feature study and preparation, mathematical/statistical modeling, performance validation, support for model deployment to production, and measurement of results. • Collaborate with the functional area in the design, application and monitoring of models. • Work in a dynamic, constantly evolving environment, interacting with professionals of different profiles and seniority levels.

Role Description We are seeking a Statistician to join our Data Analytics team. In this role, the Statistician will provide statistical and analytical support for healthcare data analysis projects using a variety of statistical methods and analytical tools. Working under the guidance of senior analytical staff, the Statistician will develop, analyze, and interpret complex datasets to support program integrity, healthcare operations, and business decision-making. This position works both independently and collaboratively with data analysts, statisticians, and project leadership to produce high-quality deliverables for clients. Responsibilities - Perform data extraction, cleaning, validation, transformation, and maintenance across multiple data sources. - Conduct statistical analyses and quantitative data mining to identify trends, patterns, anomalies, and other meaningful insights. - Develop reports, dashboards, summaries, and visualizations to communicate analytical findings. - Compile, validate, interpret, and present data to support operational and business objectives. - Perform statistical programming and data analysis using analytical software and programming languages. - Design and execute database queries to retrieve and analyze data from large datasets. - Prepare clear, concise, and accurate reports, memoranda, data files, and presentations for internal and external stakeholders. - Communicate analytical methods, assumptions, and results to both technical and non-technical audiences. - Support internal quality reviews, audits, and data validation activities. - Participate in team projects, methodology discussions, and continuous process improvement initiatives. - Stay current on statistical methods, healthcare industry trends, data analytics technologies, and applicable regulations. - Perform ad hoc analyses and other duties as assigned. - Maintain compliance with all applicable privacy, security, and confidentiality requirements. - Adhere to IntegrityM policies and client requirements governing the protection of sensitive information. Qualifications - Bachelor's degree in Statistics, Biostatistics, Mathematics, Computer Science, Data Science, or a related quantitative field. - Minimum of two years of experience using statistical programming languages (e.g., SAS, Python, R, or SQL). - Preferred experience with statistical methodologies and relational databases. - Minimum of three years of experience analyzing healthcare, health insurance, or government healthcare program data. - Preferred experience working with healthcare claims, clinical, financial, or administrative datasets. - Advanced knowledge of statistical analysis, quantitative methods, and analytical problem solving. - Proficiency with Python, Databricks, SAS, SQL, Excel, Word, PowerPoint, and other analytical tools. - Experience developing queries, analyzing large datasets, and interpreting complex data. - Strong written and verbal communication skills with the ability to explain technical concepts to non-technical audiences. - Strong organizational, analytical, and problem-solving skills. - Ability to work independently while collaborating effectively within a multidisciplinary team. - Ability to manage multiple priorities and meet established deadlines. - Passion for supporting healthcare program integrity and IntegrityM's mission, vision, values, and operating principles. Benefits - Vacation - Sick leave - Paid holidays - Health insurance - Dental insurance - Vision insurance - Short- and long-term disability - Life insurance - Employee assistance plan - 401(K) retirement plan - Educational benefits