Title: Senior Data Scientist Locations: Malvern, PA Philadelphia, PA Charlotte, NC time type Full time hybrid job requisition id 173915 Job Description: Role Summary This role leads and executes deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making, while mentoring junior data scientists and analysts, and applying advanced data science and big data mining techniques to uncover trends, inform strategic initiatives, and drive innovation across diverse business functions. Responsibilities - Develop end-to-end Generative AI solutions leveraging LLMs and foundational AI components - Design and implement scalable RAG (Retrieval-Augmented Generation) workflows - Develops complex queries and performs extensive programming to access, transform, and prepare data for statistical modeling. - Leads and executes deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making. Mentors and develops junior data scientists and analysts. - Identifies and diagnoses data inconsistencies and errors, documents data assumptions, and forages to fill data gaps. - Engages with internal stakeholders to understand and probe business processes in order to develop hypotheses. Brings structure to requests and translates requirements into an analytic approach. - Guides test design, research design, and model validation. Provides statistical consultation services. Serves as the analytics expert on cross functional teams for large strategic initiatives and contributes to the growth of the Vanguard analytic community. - Prepares and delivers insight presentations and action recommendations. Communicates complex analytical findings and implications to business leaders. - Participates in special projects and performs other duties as assigned. - Designs scalable data mining models and reporting protocols to identify trends and patterns in massive datasets. - Applies modern and emerging data science techniques to solve business problems across functions such as marketing, economics, and operations. - Contributes to the advancement of analytics through exploratory research and application of cutting-edge statistical theory. Qualifications and Skills - Minimum 8 years of experience in data science, predictive analytics, or advanced statistical modeling roles - Bachelor’s degree (B.E./B.Tech) in Analytics, Applied Mathematics, Economics, Statistics, or Computer Science, or a Master’s degree/Diploma in a related quantitative field - Expertise in programming with Python, R, or SQL; hands-on experience with machine learning libraries (e.g., Scikit-learn, TensorFlow); strong understanding of data pipelines, data wrangling, and statistical techniques; experience in big data environments (Spark/Hadoop); familiarity with visualization tools like Tableau or Power BI Special Factors Sponsorship Vanguard is not offering visa sponsorship for this position. About Vanguard At Vanguard, we don't just have a mission—we're on a mission. To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best. How We Work Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

Job Title: Data Scientist Location: DDMI - Okemos Full time Job Description: Location Specifics: Hybrid Position Job Summary: At Delta Dental of Michigan, Ohio, and Indiana we work to improve oral health through benefit plans, advocacy and community support, and we amplify this mission by investing in initiatives that build healthy, smart, vibrant communities. We are one of the largest dental plan administrators in the country, and are part of the Delta Dental Plans Association, which operates two of the largest dental networks in the nation. At Delta Dental, we celebrate our All In culture. It’s a mindset, feeling and attitude we wrap around all that we do – from taking charge of our careers, to helping colleagues and lending a hand in the community. Position Description: To implement quantitative and predictive models, data science experiments using literate programming techniques such as Python Jupyter Notebooks, develop appropriate visualizations of data, curate and prepare data using appropriate programmatic and non-programmatic data transformation techniques, continuously learn new techniques and methods to improve data science outcomes. Primary Job Responsibilities: - Develops and implements advanced statistical models using casual modelling, machine learning and optimization techniques. - Leads the team incorporating new Data Science techniques to enhance the organization's best practices. - Applies machine learning algorithms and predictive models to solve complex business challenges. - Designs and conducts data-driven experiments to validate findings and hypotheses. - Communicates insights and results to senior stakeholders and decision-makers. - Develops innovative approaches to data collection and validation, incorporating both structured and unstructured data sources. Perform other related assigned duties as necessary to complete the Primary Job Responsibilities as described above. #LI-Hybrid Minimum Requirements: Position requires a bachelor's degree in Computer Science, Mathematics, Statistics, or other quantitative field with a master’s degree in Data Science, Business Analytics, Health Informatics, or related field preferred, and three years of experience working extensively with data. Knowledge of health or dental insurance, or of dental clinical practice preferred. Position requires experience in statistical modeling methods, machine learning algorithms, supervised and unsupervised learning, and data mining techniques; proficiency with statistical software packages like SAS, R, or equivalent preferred; experience with programming languages, especially Python and SQL, or equivalent; excellent communication skills and the ability to clearly and concisely communicate complex information to a variety of audiences, both technical and non-technical; the ability to collaborate in a team. The company will provide equal employment and advancement opportunity within the context of its unique business environment without regard to race, color, religion, gender, gender identity, gender expression, age, national origin, familial status, citizenship, genetic information, disability, sex, sexual orientation, marital status, pregnancy, height, weight, military status, or any other status protected under federal, state, or local law or ordinance.

Role Description We're hiring a Senior or Staff-level Data Scientist to help design and build the powerflow and optimisation engines at the core of our platform. This role sits at the heart of our work on calculating safe, real-time capacity for distributed energy resources within network constraints and turning those calculations into forecasts and dispatch, resource allocation, and grid management decisions that affect how networks actually operate. This is applied optimisation work. You'll formulate constrained optimisation problems, implement algorithms, and build systems that run in real-time or near-real-time operational contexts. You'll work closely with the rest of the Grid Modelling team to translate network physics into optimisation constraints and get solutions into production. What you'll do - Develop powerflow engines for grid modelling and forecasting - Solve constrained optimisation problems related to grid operations, resource dispatch, and network management - Design optimisation solutions that balance multiple objectives (safety, efficiency, customer impact, operational constraints) - Collaborate with others in the grid modeling team to formulate network models and constraints as optimisation problems - Build scalable optimisation solutions that perform in real-time or near-real-time operational contexts - Establish best practices for optimisation model development, validation, and monitoring - Contribute to technical strategy for data science, optimisation capabilities and future applications Qualifications - Powerflow and/or optimisation expertise - Deep experience with one or both of: - AC optimal powerflow (AC-OPF) calculations, including the use of key open-source packages such as OpenDSS, pandapower and lf-energy - Constrained optimisation, operations research, or similar fields (linear programming, convex optimisation, mixed-integer programming, familiarity with optimisation solvers and frameworks such as Pyomo, CBC, Gurobi, CPLEX, OR-Tools, etc.) - Data science foundations: Statistical modeling, numerical programming, algorithm design, data analysis - Senior/Staff level experience: 5+ years in data science/ML/optimisation roles with demonstrated impact - Python proficiency: Capable of writing quality code for optimisation algorithms and data analysis; familiar with architectural principles, system design, version control, testing practices, code review, CI/CD Requirements - Grid domain knowledge (electrical networks, power systems, operational constraints) - Experience with market dispatch, energy economics, or resource scheduling problems - Real-time or near-real-time optimisation system experience - Understanding of DER integration challenges and VPP operations - Experience in highly parametric statistical model fitting, e.g. state estimation for energy networks - Experience with optimisation in high-performance contexts, e.g. use of metaheuristics, HPC - Experience in load forecasting - Ability to work with customers to incorporate their existing forecasts into your own calculations - Software engineering depth (system design, testing, deployment, MLOps) - Familiarity with Databricks - Familiarity with data cleaning and data exploration Benefits - $160k–$220k depending on experience, plus equity - Remote-first, with head office in Sydney - A talented team of engineers, data scientists, and power systems specialists working on hard problems that matter Sound interesting? We'd love to hear from you! Apply directly and we'll be in touch shortly.

Role Description We’re looking for an Associate Clinical Data Manager (ACDM) based in Costa Rica to support the acquisition, quality, and compliance of external clinical trial data across multiple studies. - Support the end‑to‑end acquisition of third‑party (non‑EDC) clinical data for assigned studies - Ensure data integrity, quality, compliance, and audit readiness throughout the data lifecycle - Collaborate with external vendors to align on timelines, processes, and issue resolution - Partner with cross‑functional study teams to support study objectives - Monitor data deliverables and proactively identify and resolve risks or inconsistencies - Represent ACDM activities in study team meetings, audits, and inspections - Support and informally train coordinators and peers on study and vendor‑specific considerations - Contribute to process improvements and data integration optimization initiatives Qualifications - 3–5 years of experience in Clinical Data Management and/or drug development - Experience supporting third‑party clinical data acquisition and vendor oversight - Solid understanding of clinical trial processes, ICH‑GCP, and global regulatory requirements - Clinical data standards (CDISC, SDTM, ADaM) and data governance practices - Non‑EDC data sources and data integration processes - Strong organizational, problem‑solving, and project coordination skills - Effective communication and collaboration across functional teams - High attention to detail and commitment to quality and compliance Requirements - BS/BA required, preferably in Life Sciences, Health, Technology, or equivalent experience Important - This position requires candidates to be based in Costa Rica Benefits - Exposure to multiple therapeutic areas and development phases - Collaboration with global teams and innovative data technologies - Opportunity to make a meaningful impact on clinical development programs