• Understanding the data which our clients provide to us; • Cleaning that data and validating that it is correct; • Preprocessing the data, usually by using a mixture of shell scripts and a programming language such as Python, Java, Scala, etc; • Iteratively computing features and tuning parameters to improve the quality of the model; • Communicating your findings to the project manager and assisting him/her in decision making on the Data Science part of the project; • Work together with key stakeholders (data scientists, engineers, risk managers) from our clients; • Work with other parts of the organization (Product, Research, etc.) to improve processes, best practices and tooling.

Role Description If you’re a talented Data Scientist looking to be part of a fast-growing, innovative R&D team, shape the future of decision-making in business, work on cutting-edge technologies and vast amounts of global real-time data, affect billions of mobile users, and become an industry leader - then let’s talk! Start.io is a mobile data platform that enables organizations to uncover insights and make data-driven decisions that enhance strategies and drive growth. We are seeking a Senior Data Scientist to join our Data Science & Engineering team. - Analyze large and complex data to discover hidden patterns and opportunities; - Develop and own end-to-end highly scalable data pipelines; - Develop state-of-the-art machine learning models, and algorithms and build solutions in monetization fields; - Provisioning data models for real-time (online) processing; - Shape new data products, and constantly improve the existing products; - Collaborate with multiple teams including Product, BI, Analysts, DevOps, R&D and Marketing to lead and accomplish overall solutions; - Oversee a complete release to production, including analyzing requirements, testing, monitoring and measuring results, multitasking, and quickly responding to critical issues. Qualifications - B.Sc./M.A/M.Sc. degree in Computer Science, Engineering, Math, Statistics, or other equivalent fields; - 6 years as a Data Scientist - a strong background in ML concepts and models; - Hands-on experience with Python, especially with data science ML libraries (regression & classification algorithms e.g. XGB or LGBM, recommendation system algorithms, etc.); - Understanding of databases and SQL for data retrieval; - Monitoring and alerting tools (e.g. Grafana, Kibana). Requirements - Knowledge in the programmatic advertising landscape – DSPs, SSPs, exchanges – significant advantage; - Experience with relational (e.g. Vertica, VoltDB) and non-relational (e.g. MongoDB) databases; - Experience with PMML. Benefits - Help and support from our caring HR team; - 20 days of vacation; - The exchange of experience and work with talented colleagues; - Last but not least - valuable compensation for your efforts.

• Design, build, and maintain R Shiny applications for clinical study monitoring, data visualization, safety review, and exploratory analysis • Develop modular, scalable, and well‑documented R code following best practices • Create interactive dashboards, visualizations, and bespoke analytical tools for cross‑functional teams • Optimize Shiny app performance, security, and usability for deployment in regulated environments • Ensure all deliverables comply with CDISC standards, regulatory guidance, and internal SOPs • Act as a subject matter expert (SME) for R and R Shiny within the team • Mentor junior programmers and contribute to knowledge‑sharing initiatives • Participate in study meetings, providing technical insights and programming expertise • Influence best practices, pipelines, and automation strategies for modernizing statistical workflows

Title: Data Scientist Supervisor Location: Alhambra, California, 91803, United States Department: Program Positions Job Category: Program Positions Requisition Number: DATAS006318 Full-Time Hybrid Job Description: Salary Range: $9,852.82 - $13,278.10 Monthly SUMMARY The Data & Analytics Unit is responsible for collecting, analyzing, and interpreting healthcare data to support decision-making across the Los Angeles County Department of Health Services (DHS). The unit manages patient care and operational data, using analytics to identify patterns, predict outcomes, and improve service delivery. The unit also ensures data integrity, security, and regulatory compliance. The Data Scientist Supervisor leads a team of data scientists within the DHS Data & Analytics Unit, overseeing the execution of advanced analytical projects, machine learning initiatives, and data-driven strategies. This role is responsible for managing the development and implementation of predictive models, optimizing data workflows, and ensuring that analytical solutions align with organizational objectives. The Data Scientist Supervisor provides technical leadership, mentors team members, and fosters a collaborative environment to drive innovation and efficiency in data science operations. ESSENTIAL FUNCTIONS - Team Leadership & Mentorship - Lead, coach, and mentor data scientists, fostering a culture of continuous learning and professional growth. - Project Oversight & Execution - Manage and oversee the development of machine learning models and analytical solutions to meet business needs. - Apply advanced statistical methods, machine learning algorithms, and data mining techniques to analyze large and varied datasets, uncovering trends and patterns that provide actionable insights. - Fine-tune and optimize models, ensuring they are scalable, efficient, and aligned with business requirements. - Mentor junior data scientists and guide their model development, statistical analysis, and data science practices. - Data Engineering & Workflow Optimization - Collaborate with engineering teams to ensure the scalability, efficiency, and accuracy of data pipelines. - Quality Assurance & Best Practices - Establish and enforce best practices in data science methodologies, model validation, and documentation. - Advanced Data Analysis & Modeling - Lead the development of predictive, prescriptive, and diagnostic models to address complex business problems and optimize decision-making processes. - Machine Learning & AI Implementation - Design, train, and optimize machine learning models for forecasting, anomaly detection, and automation. - Insightful Reporting & Visualization - Create and deliver high-quality, clear, and actionable reports and dashboards, translating complex data findings into easily understandable insights for both technical and non-technical stakeholders. - Use advanced visualization tools and techniques to convey analytical results effectively to leadership and business teams. - Develop and implement metrics and KPIs that measure the effectiveness of data science initiatives and model performance. - Strategic Collaboration & Stakeholder Engagement - Work closely with business leaders and stakeholders to define data-driven strategies and deliver actionable insights. - Translate complex technical concepts into actionable business insights and recommendations for non-technical audiences. - Partner with IT, engineering, and business teams to integrate data science solutions into operational processes. - Continuous Improvement & Research - Stay abreast of emerging data science techniques, industry trends, and technologies to drive innovation within the team and ensure best-in-class data science practices. - Lead research initiatives that explore new methods for data analysis, modeling, and automation. - Continuous improvement of data science workflows, techniques, methodologies, new tools, and technologies within the organization. JOB QUALIFICATIONS The ideal candidate is a seasoned data science professional with strong leadership skills, a track record of managing data science projects, and the ability to translate complex analytics into strategic business recommendations. They should possess a combination of technical expertise, team management experience, and a deep understanding of machine learning and data-driven decision-making. Education/Experience - Master’s degree from an accredited institution in Data Science, Computer Science, Statistics, Mathematics, or a related field. - 6+ years of experience in data science, with at least 2 years in a leadership role. - Extensive hands-on experience in machine learning, AI, and predictive modeling. Proven experience leading and mentoring data science teams. Certificates/Licenses/Clearances - Successful clearing through the Live Scan process with the County of Los Angeles. Other Skills, Knowledge, and Abilities - Advanced programming skills in Python, R, and SQL for model development and data processing. - Expertise in cloud computing (AWS, Azure, GCP) and big data technologies. - Strong experience with data visualization tools (Tableau, Power BI) for storytelling and reporting. - Deep knowledge of data engineering concepts, ETL processes, and model deployment. - Proven ability to lead data science projects from ideation to implementation. - Excellent communication skills to present complex insights to both technical and non-technical audiences. - Experience mentoring junior data scientists and fostering a data-driven culture. - Strong understanding of agile methodologies and project management principles. - Commitment to innovation and staying at the forefront of industry trends. PHYSICAL DEMANDS Stand: Not applicable Walk: Not applicable Sit: Frequently Handling / Fingering: Constantly Reach Outward: Constantly Reach Above Shoulder: Not applicable Climb, Crawl, Kneel, Bend: Not applicable Lift / Carry: Occasionally - Not applicable Push/Pull: Occasionally - Not applicable See: Constantly Taste/ Smell: Not Applicable Not Applicable = Not required for essential functions Occasionally = (0 - 2 hrs/day) Frequently = (2 - 5 hrs/day) Constantly = (5+ hrs/day) WORK ENVIRONMENT Hybrid EEOC STATEMENT Heluna Health is an Affirmative Action, Equal Opportunity Employer that encourages minorities, women, veterans, and disabled to apply. It is the policy of Heluna Health to provide equal employment opportunities without regard to race, color, religion, sex, national origin, age, disability, marital status, veteran status, sexual orientation, genetic information or any other protected characteristic under applicable law.