Role Description This role offers a unique opportunity to work at the intersection of data science, software engineering, and public impact by building an innovative proof-of-concept solution aimed at improving critical intake processes. You will leverage advanced machine learning and natural language processing techniques to design and validate a system that enhances decision-making while optimizing resource allocation. Collaborating closely with stakeholders and cross-functional teams, you will help translate complex requirements into actionable solutions. The position involves hands-on development, experimentation, and demonstration of a prototype application in a highly collaborative, Agile environment. Your work will directly contribute to improving outcomes through data-driven insights and technology innovation. This is an ideal opportunity for someone who thrives on solving complex problems with measurable real-world impact. - Design, develop, and implement machine learning models and NLP-driven solutions to improve intake processes and outcomes - Collaborate with stakeholders and technical teams to gather requirements, ensure transparency, and validate statistical soundness - Analyze current workflows, identify inefficiencies, and propose data-driven improvements to optimize resource allocation - Identify, evaluate, and integrate internal and external data sources into the solution architecture - Build and refine a proof-of-concept prototype application using technologies such as Python, Java, C++, SQL, and modern frameworks - Conduct testing, validation, and performance measurement of models and applications in both pilot and simulated environments - Present findings, demonstrate the prototype, and gather feedback through stakeholder workshops and live demonstrations - Ensure data security and compliance, especially when leveraging LLMs or sensitive data sources - Participate actively in Agile development processes to ensure timely and high-quality delivery Qualifications - Bachelor’s or Master’s degree in Computer Science, Engineering, Physics, or a related field - 5+ years of experience in data science, software development, or related roles - Proven expertise in building AI/ML solutions from the ground up, including NLP and LLM integration - Strong foundation in mathematics, including calculus, linear algebra, and statistics; advanced topics are a plus - Experience designing custom machine learning models and statistical methods without heavy reliance on pre-built libraries - Proficiency in programming languages such as Python, C++, Java, and familiarity with frameworks like React, Node.js, and Next.js - Solid experience with databases such as PostgreSQL, MySQL, or SQL Server, and cloud platforms like AWS - Demonstrated experience deploying analytic models in pilot or production environments - Strong understanding of model validation, evaluation metrics, and performance optimization - Excellent communication skills with the ability to engage both technical and non-technical stakeholders - Experience working in public sector or regulated environments is highly preferred Benefits - Competitive compensation package - Paid sick leave - Comprehensive health coverage including medical, dental, vision, and life insurance - 401(k) plan with employer matching - Health Savings Account (HSA) options - Short-term and long-term disability coverage - Inclusive and equal opportunity workplace supporting diversity and accessibility

• Own Mercuryo's Voice of the Customer programme and turn customer insights into business improvements. • Identify customer pain points using support data, feedback, CSAT, and operational metrics. • Drive initiatives that reduce customer contacts through product improvements, automation, and self-service. • Own the performance and optimisation of Forethought AI to improve automation and customer experience. • Build dashboards and provide actionable insights on customer satisfaction, support performance, and AI effectiveness. • Own Mercuryo's Help Centre and internal knowledge base. • Lead our White Glove VIP Support Programme and manage the VIP Relationship Specialist. • Partner with Product, Engineering, Customer Support, and other teams to improve the end-to-end customer journey.

Role Description We are seeking a Freelance Data Scientist with availability to handle multiple projects, who can lead complex data initiatives, design robust models, and influence product and business decisions through data. This position starts as a part-time position and has the potential to become a full-time employee depending on performance. Hourly salary will be determined based on experience and skill level. This role requires deep expertise in statistics, machine learning, and data modeling, along with the ability to mentor others, define best practices, and work closely with engineering, product, and leadership teams. Exposure to modern AI and LLM-based systems is a strong plus. Qualifications - Expert-level proficiency in Python (Pandas, NumPy, Scikit-learn) - Strong foundation in statistics, probability, and linear algebra - Extensive experience with machine learning techniques (regression, classification, clustering, time-series, anomaly detection) - Strong hands-on experience with SQL and relational databases - Experience working with large datasets and complex data pipelines - Deep understanding of model evaluation, bias/variance trade-offs, and performance monitoring - Proven experience taking models from development to production Requirements - Lead end-to-end data science projects from problem definition to production deployment - Design, build, and optimize advanced statistical and machine learning models - Analyze large-scale, structured and unstructured datasets to generate actionable insights - Define data science best practices, modeling standards, and evaluation frameworks - Design and analyze experiments (A/B tests, causal analysis, hypothesis testing) - Partner with product, engineering, and business stakeholders to influence strategy and roadmap - Review and improve existing models for accuracy, scalability, and robustness - Mentor junior data scientists and review analytical work - Clearly communicate complex findings to senior stakeholders and leadership - Ensure data quality, reproducibility, and documentation across projects Benefits - Hands-on experience with Large Language Models (LLMs) such as GPT, Claude, LLaMA, or similar - Experience integrating LLM APIs into production systems - Strong understanding of prompt engineering and output evaluation - Experience with embeddings, semantic search, and vector similarity techniques - Knowledge of Retrieval-Augmented Generation (RAG) architectures - Experience working with vector databases (Pinecone, FAISS, Weaviate, Milvus, etc.) - Awareness of AI risks such as hallucinations, bias, security, privacy, and cost optimization Education - Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field - Equivalent real-world experience is highly valued

• Support large-scale data analysis • Evaluate product and program performance • Enable data-driven decision-making across the organization • Work closely with Product, Engineering, and Business teams to deliver actionable insights • Contribute to the development of reliable internal data infrastructure • Analyze user behavior and engagement trends • Design metrics and analytical frameworks to evaluate feature performance • Develop and deploy models for prediction and segmentation • Build feature pipelines and implement model monitoring • Establish consistent metric definitions and reporting standards • Promote best practices in data governance and reproducible analytics