Senior/Lead Data Scientist

At CloudFactory, we are a mission-driven team passionate about unlocking the potential of AI to transform the world. By combining advanced technology with a global network of talented people, we make unusable data usable, driving real-world impact at scale. More than just a workplace, we’re a global community founded on strong relationships and the belief that meaningful work transforms lives. Our commitment to earning, learning, and serving fuels everything we do as we strive to connect one million people to meaningful work and build leaders worth following. Our Culture At CloudFactory, we believe in building a workplace where everyone feels empowered, valued, and inspired to bring their authentic selves to work. We are: Mission-Driven: We focus on creating economic and social impact. People-Centric: We care deeply about our team’s growth, well-being, and sense of belonging. Innovative: We embrace change and find better ways to do things together. Globally Connected: We foster collaboration between diverse cultures and perspectives. If you’re passionate about innovation, collaboration, and making a real impact, we’d love to have you on board Role Summary As a Lead Data Scientist you will be accountable for managing a team of data scientists, leading complex data science projects, driving innovation in data-driven decision-making and building analytics models to extract valuable insights from data that align with the purpose of CloudFactory. Responsibilities Machine Learning & AI Development: Design, train, and deploy advanced machine learning models for predictive insights. Enhance automation and optimize analytics methodologies for improved efficiency. Develop & Monitor Performance Models: Build predictive models to assess user and team performance, growth, and churn. Design analytics for customer health, behavioral trends, and upgrade/downgrade probabilities. Fraud Detection & Prevention: Lead efforts in fraud analytics, refining detection models and developing proactive strategies to mitigate risk and identify anomalies in data behavior. Research & Innovation in Data Science: Explore new methodologies/LLMs/GenAI to improve data-driven decision-making. Volume Forecasting: Predict future workload volumes based on historical data and trends to optimize resource allocation. Develop a deep understanding of business performance levers, adding insight to information and helping to form recommendations as to how to improve overall performance of the platform business. Prepare and present compelling visual representations of the analysis that is easy to share and understand, with various stakeholders from exec level down. Team Leadership Oversee and guide a team of data scientists. Provide technical mentorship to junior data scientists. Support the professional development of the data science team. Collaborate with stakeholders to align AI solutions with business goals and operational strategies. Work closely with the wider Data Science, Product and Tech teams to provide collaborative insight on customer behaviour across our products. Knowledge Demonstrates competence in performing core data science tasks independently. Can select appropriate machine learning algorithms, train and evaluate models, and interpret basic results. Can independently clean and prepare data for analysis using established techniques. Can select and apply machine learning algorithms (e.g., linear regression, k-nearest neighbors) to solve specific problems. Can train and evaluate models using appropriate metrics (e.g., accuracy, precision, recall) and identify basic performance issues. Can create data visualisations to communicate model results and insights to stakeholders. Strong analytical and problem-solving skills are essential. Skills and Experience Must Have: 8+ years of hands‑on experience in leading and implementing core data science projects, including a minimum of 2+ years of experience mentoring or managing data science/analytics teams. Expertise in advanced SQL for data extraction, manipulation, and analysis. Hands‑on experience with Snowflake, including data warehousing, performance optimisation, and query tuning to ensure efficient data retrieval and management. Strong proficiency in Python, including production‑level coding and statistical packages. Solid background in Statistical Modeling, Time Series Analysis, Machine Learning, and AI. Deep understanding of cloud platforms (AWS/Azure/GCP) and big‑data tools (Spark, Databricks, Snowflake). Hands‑on experience with Docker, AWS Lambda, SageMaker, Airflow/Prefect for pipeline automation. Strong ability to assess the application of machine learning & statistical techniques for appropriate usage and evaluation. Well‑versed in data engineering concepts, including data transformation, modelling, ETL pipelines. Expertise in data visualisation and storytelling for impactful business insights. Good-to-Have: Experience in developing dashboards using Tableau or QuickSight. Familiarity with data integration tools like Fivetran and DBT. Benefits Great Mission and Culture Meaningful Work Market competitive salary Quarterly variable compensation Remote and Home working Comprehensive medical cover Group life insurance Personal development and growth opportunities Office snacks and lunch Periodic team building and social events At CloudFactory, we believe that work should be more than just a job—it should be a platform for growth, impact, and community. Here, you’ll earn with purpose, learn every day, and serve a mission that truly matters. If you're looking for a career where you can develop professionally, contribute meaningfully, and be part of a global movement, we’d love to have you on this journey Join us today and be part of our mission to connect people and technology for a better world Apply now and bring your whole, authentic self to work—we can’t wait to meet you #J-18808-Ljbffr