• Develop and lead the organization's learning measurement and analytics strategy, ensuring alignment with business objectives and performance outcomes • Define and maintain standards for evaluating learning programs, including data collection methods, measurement frameworks, and reporting requirements • Design and implement scalable evaluation methodologies to measure behavior change, business impact, and learning effectiveness using frameworks such as Kirkpatrick Levels 3 and 4 and Phillips ROI • Build and manage learning analytics infrastructure and measurement platforms using tools such as Performativ, Qualtrics, or similar solutions • Integrate learning data with operational, talent, and business performance metrics to provide a comprehensive view of learning effectiveness • Conduct ROI analyses and advanced evaluation studies to assess the value and impact of learning initiatives • Design and execute structured evaluations, pilot programs, controlled experiments, and outcome studies to support evidence-based decision-making • Define evaluation methodologies, sampling approaches, comparison groups, and success metrics to ensure analytical rigor and validity • Perform statistical analyses using tools such as SPSS, Python, R, or equivalent analytical platforms • Develop executive-level dashboards, scorecards, and reports that communicate learning outcomes, business impact, and value realization • Translate complex analytical findings into clear, concise recommendations and business insights for senior leaders and stakeholders • Establish consistent measurement language and reporting standards focused on outcomes, performance improvement, and business value • Partner with stakeholders during project planning to define success measures, evaluation strategies, and business impact goals • Provide consultation and guidance on measurement design, data collection strategies, and interpretation of analytical findings • Develop reusable tools, templates, frameworks, and best practices to standardize learning measurement across the organization • Conduct external benchmarking and research to compare learning effectiveness against industry standards and leading practices • Build organizational capability in learning analytics and measurement through coaching, knowledge sharing, and stakeholder education • Influence leaders and business partners on the effective use of data, evidence, and measurement practices to support decision-making

Design and deploy predictive models and machine learning solutions, mentor junior data scientists, collaborate with cross-functional teams to translate analysis into actionable insights, and conduct deep-dive analyses for consumer insights generation.

Title: Data Coordinator Location: Denver, CO, USA - 1721 E 19th Avenue (J012) Full time Hybrid Job Description: It’s More Than a Career, It’s a Mission. Our people are the foundation of our success. By joining our growing team at Sarah Cannon Research Institute (SCRI), a subsidiary of McKesson, you will have the opportunity to become part of one of the largest community-based cancer programs to advance oncology treatments and improve outcomes for cancer patients across the globe. We look for mission-driven candidates who have a desire to advance the fight against cancer and make a difference in the lives of patients diagnosed with cancer every day. Our Mission People who live with cancer – those who work to prevent it, fight it, and survive it – are at the heart of every decision we make. Bringing the most innovative medical minds together with the most passionate caregivers in their communities, we are transforming care and personalizing treatment. Through clinical excellence and cutting-edge research, SCRI is redefining cancer care around the world. The Data Coordinator provides support to the Clinical Research Coordinator (CRC) and Research Nurse on a daily basis, ensures all activities are conducted according to company standard operating procedures (SOPs) and all applicable Good Clinical Practice (GCP) and ICH regulations and guidelines. - You will support CRC to meet industry trial data deadlines - You will obtain source documentation for patients enrolled onto clinical trials - You will assist CRC with case report form completion and with query resolution - You will assist in Serious Adverse Event (SAE) reporting and tracking - You will create and maintain patient visit tracking spreadsheets for CTS - You will maintain and archive study administrative files - You will maintain and archive regulatory files - You will assist in ensuring source document templates are accurate. - You will be assigned special procedural projects to enhance the functioning of the research program - Throughout the conduct of the clinical trial you will assess adherence to SCRI SOPS, Good Clinical Practice (GCP) and ICH regulations and guidelines. What you should have for this role: - Knowledge of scientific, medical, and regulatory terms Knowledge of GCP and Good Manufacturing Practice (GMP) - Detail-oriented - Excellent English written and oral skills. - Bachelor Degree preferred. - Healthcare experience, Clinical trials support, or pharmaceutical industry experience preferred The compensation range for this position is $24/hr - $27/hr. About Sarah Cannon Research Institute Sarah Cannon Research Institute (SCRI) is one of the world’s leading oncology research organizations conducting community-based clinical trials. Focused on advancing therapies for patients over the last three decades, SCRI is a leader in drug development. In 2022, SCRI formed a joint venture with former US Oncology Research to expand clinical trial access across the country. It has conducted more than 850 first-in-human clinical trials since its inception and contributed to pivotal research that has led to the majority of new cancer therapies approved by the FDA in the past decade. We care about the well-being of the patients and communities we serve, and that starts with caring for our people. That’s why we have a Total Rewards package that includes comprehensive benefits to support physical, mental, and financial well-being. Our Total Rewards offerings serve the different needs of our diverse colleague population and ensure they are the healthiest versions of themselves. As part of Total Rewards, we are proud to offer a competitive compensation package. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson’s (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates.

Title: Data Scientist Location: London England GB Job Description: Hybrid Technology Full time London, England, United Kingdom OverviewApplication Description Kroo Bank is charting the future of banking through technology, data, and innovation. As a digital first bank, we use data science to help us make smarter decisions, improve customer outcomes, and build products that customers trust and love. The rapid pace of change within fintech creates exciting opportunities to apply advanced analytics, machine learning, and experimentation to real business challenges. As a Data Scientist, you will play a key role in helping Kroo use data more effectively across a wide range of business areas, partnering with teams across Product, Risk, Operations, Compliance, and Engineering. This role is responsible for building, evaluating, and deploying data science solutions that support strategic decision making and improve customer experiences. You will work on high impact initiatives across areas such as credit risk, fraud prevention, customer engagement, and operational efficiency, helping the business make informed decisions through robust analysis, experimentation, and modelling. How you'll contribute: - Build and iterate on statistical and machine learning models to solve business problems across areas such as credit risk, fraud, customer engagement, and operational efficiency. - Partner with stakeholders to define problem statements, success metrics, data requirements, and practical implementation plans. - Conduct data exploration and feature engineering to uncover drivers of outcomes and improve model performance and interpretability. - Develop robust evaluation frameworks, including appropriate baselines, validation strategies, monitoring metrics, and model performance reporting. - Support deployment of models into production in collaboration with Engineering, contributing to reproducible pipelines and model documentation. - Monitor models in production, identify performance drift, propose improvements, and support ongoing recalibration or retraining where required. - Apply probability and statistical inference to design experiments, interpret results, and provide clear recommendations to stakeholders. - Contribute to high quality data practices by identifying data quality issues, supporting cleaning and normalisation approaches, and defining standards for reliable datasets. - Write maintainable, well tested Python code using common data science libraries, and follow engineering best practices appropriate for production systems. - Use SQL and dbt to extract, transform, and validate data for analysis and modelling, ensuring traceability and reliability of outputs. - Collaborate with Risk, Compliance, and Audit stakeholders to ensure data science work is appropriately governed, documented, and aligned with regulatory expectations. - Support continuous improvement across data science methodologies, tooling, and ways of working. Requirements Required skills and behaviours: - Experience building and evaluating statistical and machine learning models in a commercial environment. - Strong analytical and problem solving skills with the ability to translate business challenges into practical data science solutions. - Ability to conduct basic data collection by independently sourcing and defining required datasets, partnering with stakeholders to clarify data needs and ensure appropriate coverage and traceability. - Ability to perform data cleaning effectively by independently applying robust cleaning approaches, proactively identifying data quality issues, and contributing to improving data reliability and standards. - Ability to conduct basic data analysis by independently performing exploratory analysis and statistical investigation, translating findings into clear insights and actionable recommendations. - Strong programming fundamentals with experience writing maintainable Python code for analysis and modelling, contributing to shared codebases through good practices, testing, and documentation. - Experience using SQL and dbt to extract, transform, validate, and analyse data. - Ability to apply visualisation techniques to produce clear, purposeful visualisations and model performance summaries that support decision making across technical and non technical audiences. - Ability to communicate effectively by explaining complex analytical concepts clearly and tailoring messages to a wide range of stakeholders. - Strong attention to detail, ensuring outputs are validated, reproducible, and documented in line with governance and compliance requirements. - Ability to manage data projects proficiently by planning and delivering work to agreed timelines, managing competing priorities, and contributing positively to team delivery processes. - Experience working collaboratively with Product, Risk, Operations, Compliance, and Engineering teams is beneficial. - Awareness of model governance, risk management, and regulatory considerations within a financial services environment is advantageous. Benefits Hybrid Working At Kroo Bank, we have a hybrid/ flexible policy that gives both individuals and teams a lot of freedom when it comes to using the office space to boost productivity. Our London office is a great resource to collaborate and candidates should be able to attend 1-2 days per week regularly to align with how we work at the moment. Diversity and Inclusion We wholeheartedly uphold our commitment to fostering a diverse and inclusive workplace. Every employee is highly regarded, respected, and supported without any form of judgement or prejudice. We consider Diversity, Equality, and Inclusion as fundamental pillars guiding our path in all aspects of our bank. We also ensure that reasonable adjustments are made available to all candidates throughout the recruitment process. To all Recruitment Agencies At Kroo Bank, agency resumes are strictly prohibited. Do not submit agency resumes or forward them to our job advertisements or Kroo Bank employees. Be aware that Kroo Bank will not assume any responsibility for fees incurred due to unsolicited resumes. To ensure a fair and efficient application process, all candidates are kindly requested to submit their applications directly through the advertised platform. We kindly ask that you refrain from reaching out to the company or its employees via email, LinkedIn, or any other communication channels for inquiries or updates. Please note that any attempts to contact us through these channels will not receive a response. Thank you for your understanding and cooperation.