76 to 100 of 333 Predictive Modelling Jobs

dynamic (Power BI) dashboards that provide clear, actionable insights into workforce metrics and financial performance. Your expertise will directly influence workforce strategy by enabling accurate forecasting, cost analysis, and predictive analytics. KEY RESPONSIBILITIES: Advanced Data Analytics & Reporting Extract, clean, transform, and integrate large datasets from internal HR systems (e.g., SAP SuccessFactors), finance platforms, and external labour market sources to … automation, macros, and complex formulas to complement data workflows. Perform deep-dive analyses to identify trends, anomalies, and opportunities in workforce supply, demand, cost drivers, and financial performance. Implement predictive analytics models to forecast workforce needs, turnover risks, skill gaps, and financial impacts. Translate complex data findings into clear, concise insights and recommendations tailored for both technical and business … Integration Collaborate closely with Finance, HR and Strategic Workforce Planning teams to align workforce data analytics with budgeting, headcount, and cost management processes. Support labour cost forecasting and scenario modelling by integrating workforce metrics with financial data. Provide analytical support for workforce-related business cases, cost optimization initiatives, and strategic planning. Monitor key financial KPIs and workforce performance indicators More ❯

analysis process, transforming small and large datasets into manageable formats for import into our software. You’ll also be supporting on the design and automation of data pipelines, building predictive models, and piloting new tools. We’ll teach you the environmental context - your superpower is data, code, and a knack for creating reliable, repeatable solutions. We’re looking for … measurement (Scopes 1, 2 & 3) Workflow innovation - finding and implementing more efficient, automated ways to handle large, messy datasets Support with automated reporting via templates, APIs or lightweight scripts Predictive modelling & scenario analysis to help clients plan net-zero pathways You’ll be our in-house champion for improving offline data processes, standardising imports into our platform, and … Footprint Measurement Apply the GHG Protocol (Scopes 1-3) using our in-house calculator and external factor libraries Research and validate emission factors, benchmarks and supplier disclosures Future Focus Predictive Modelling & Scenario Analysis Build simple models (regression, gap-filling) to forecast emissions and identify hotspots Build models for Net-Zero pathways and reduction strategies Automation & Reporting Support on More ❯

analysis process, transforming small and large datasets into manageable formats for import into our software. You’ll also be supporting on the design and automation of data pipelines, building predictive models, and piloting new tools. We’ll teach you the environmental context - your superpower is data, code, and a knack for creating reliable, repeatable solutions. We’re looking for … measurement (Scopes 1, 2 & 3) Workflow innovation - finding and implementing more efficient, automated ways to handle large, messy datasets Support with automated reporting via templates, APIs or lightweight scripts Predictive modelling & scenario analysis to help clients plan net-zero pathways You’ll be our in-house champion for improving offline data processes, standardising imports into our platform, and … Footprint Measurement Apply the GHG Protocol (Scopes 1-3) using our in-house calculator and external factor libraries Research and validate emission factors, benchmarks and supplier disclosures Future Focus Predictive Modelling & Scenario Analysis Build simple models (regression, gap-filling) to forecast emissions and identify hotspots Build models for Net-Zero pathways and reduction strategies Automation & Reporting Support on More ❯

science teams to create solutions for large business problems. You will collaborate closely with experienced data scientists focusing on advanced challenges such as entity resolution at scale and graph modelling with Neo4J to produce graphical representations of potential fraud rings. Our Data Scientists research and apply advanced techniques in Machine Learning, Natural Language Processing, Deep Learning, and Computer Vision … environment or completed a PhD with two years of suitable industry or research experience in a Data Science role. Strong Python skills with experience in Natural Language Processing and Predictive Modelling, alongside solid SQL capabilities. Experience in creating, deploying, and tuning complex, non-linear predictive models to solve business problems using Python and associated Data Science tooling. More ❯

spanning the globe to ensure we deliver best in class risk prevention solutions Your key responsibilities Develop a thorough understanding of the data science lifecycle, including data exploration, preprocessing, modelling, validation, and deployment. Design, build, and maintain tree-based predictive models, such as decision trees, random forests, and gradient-boosted trees, with a low-level understanding of their … accuracy and reliability of data models. Communicate complex data insights to non-technical stakeholders through clear and actionable reports. Apply domain knowledge (if applicable) in financial fraud to enhance predictive modelling and anomaly detection capabilities. Skills and attributes for success Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention More ❯

spanning the globe to ensure we deliver best in class risk prevention solutions Your key responsibilities Develop a thorough understanding of the data science lifecycle, including data exploration, preprocessing, modelling, validation, and deployment. Design, build, and maintain tree-based predictive models, such as decision trees, random forests, and gradient-boosted trees, with a low-level understanding of their … accuracy and reliability of data models. Communicate complex data insights to non-technical stakeholders through clear and actionable reports. Apply domain knowledge (if applicable) in financial fraud to enhance predictive modelling and anomaly detection capabilities. Skills and attributes for success Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention More ❯

spanning the globe to ensure we deliver best in class risk prevention solutions. Your Key responsibilities Develop a thorough understanding of the data science lifecycle, including data exploration, preprocessing, modelling, validation, and deployment. Design, build, and maintain tree-based predictive models, such as decision trees, random forests, and gradient-boosted trees, with a low-level understanding of their … accuracy and reliability of data models. Communicate complex data insights to non-technical stakeholders through clear and actionable reports. Apply domain knowledge (if applicable) in financial fraud to enhance predictive modelling and anomaly detection capabilities. Skills and attributes for success Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention More ❯

and play a key role in maximizing both customer acquisition and retention across the business. You'll work closely with growth, product, and analytics stakeholders to uncover insights, build predictive models, and drive high-impact decision-making through experimentation and forecasting. This is a high-visibility role where your work will directly influence business strategy, growth initiatives, and long … and non-technical stakeholders. Delve into large-scale datasets using SQL and perform advanced statistical techniques in Python. Continuously evaluate and improve existing models and testing frameworks to increase predictive accuracy and business impact. How Will Your Time Be Spent? 30% on Analysis - Mining and analysing customer, growth, marketing, and operations data to uncover insights that inform strategic decisions. … This includes building dashboards, running cohort analyses, and identifying trends and anomalies. 25% on Data Science & Modelling - Developing predictive models (e.g., churn prediction, CLV forecasting, segmentation models), conducting A/B test analysis, and applying machine learning to solve real business problems. Collaborating with engineers to validate and deploy models. 20% on Strategy & Stakeholder Collaboration - Partnering with marketing More ❯

investment and is integral to strategic decision-making across the business. In this role, you’ll work with large-scale, complex datasets – both quantitative and qualitative – applying statistical analysis, predictive modelling, and visualisation techniques to support business reporting, stakeholder engagement, and research projects. Why apply? Shape the future – Your insights will influence organisational strategy, thought leadership, and programme More ❯

models, analytics frameworks, and experimentation strategies across the platform. Analyze user journeys and behavioral data across tenants to uncover insights that inform product and engagement strategies. Develop segmentation and predictive models to support personalization and proactive member engagement based on demographics, behavior, and interaction activities etc. Design and analyze experiments (A/B testing, cohort studies) to assess feature … financial services sector. Skills Strong SQL skills and experience working with large, complex data sets. Proficiency in SQL and Python or R, with hands-on experience in machine learning, predictive modeling, and statistical analysis. Proven experience working directly with product analytics platforms like Mixpanel, Amplitude, or similar tools. Experience with data visualization and BI tools (e.g., Looker, Power BI More ❯

and this is a great chance to have a profound impact on the project. Key Responsibilities: Analyze large datasets to uncover patterns and insights related to customer behavior. Develop predictive models to forecast customer activities and trends. Collaborate with cross-functional teams to implement data-driven strategies. Define and track key performance indicators (KPIs). Utilize machine learning techniques … and concise manner. Requirements: Master's or PhD degree in a quantitative field. Proven experience of large-scale data analysis and hypothesis testing. Strong proficiency in statistical analysis and predictive modeling. Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. Excellent problem-solving skills and attention to detail. Strong communication skills with … might expect to work on: Predicting future expected value and future potential value of individual customers. Real-time prediction of customer churn. Building multi-level customer segmentation driven by predictive models. Here's what we offer: Start with 25 days of annual leave, with 2 additional days added each year, up to 35 days by your fifth year with More ❯

will contribute to planning, execution, interpretation, validation and communication of innovative exploratory analyses and algorithms, to facilitate internal decision making. You will provide technical expertise in data science and (predictive) machine learning/AI to identify opportunities for influencing internal decision making as well as discussions on white papers/regulatory policy. You will perform hands-on analysis of … methods, variable selection methods (e.g., lasso, elastic net, random forest), design of clinical trials. Strong programming skills in R and Python. Demonstrated knowledge of data visualization, exploratory analysis, and predictive modeling. Excellent interpersonal and communication skills (verbal and writing). Ability to develop and deliver clear and concise presentations for both internal and external meetings in key decision-making More ❯

will play a pivotal role in driving data-driven decision-making and shaping strategic initiatives. Your expertise will directly impact the organisation's ability to understand client behaviour, refine predictive models, and deliver actionable insights that influence key business outcomes. You will take on the responsibility of developing and optimising machine learning models, analysing complex datasets, and collaborating closely … will play a pivotal role in driving data-driven decision-making and shaping strategic initiatives. Your expertise will directly impact the organisation's ability to understand client behaviour, refine predictive models, and deliver actionable insights that influence key business outcomes. You will take on the responsibility of developing and optimising machine learning models, analysing complex datasets, and collaborating closely More ❯

that help with data-driven decision-making. Use R Studio for data analysis, statistical modeling, and generating insights from large datasets. Work with the data science team to build predictive models and statistical reports that meet business needs. Document processes, workflows, and configurations to ensure consistent and effective data management practices. Qualifications: Bachelor's degree in Computer Science, Information More ❯

and visualisation experts that utilise advanced statistical techniques to analyse our HR, financial and marketing data. The role encompasses discovering and rationalising historical patterns in large data sets, developing predictive models, creating automated data solutions and researching machine learning techniques that are proprietary to Unilever. It also involves working to enhance the team's infrastructure by introducing new tools More ❯

and KPIs Improve access to fraud data through collaboration with engineering and data teams Present complex data findings to stakeholders in a clear and actionable manner Model Development Create predictive models and apply machine learning techniques to identify fraud risks Continuously evaluate and enhance fraud models to maintain detection accuracy Maintain clear documentation of methodology for use across both More ❯

and KPIs Improve access to fraud data through collaboration with engineering and data teams Present complex data findings to stakeholders in a clear and actionable manner Model Development Create predictive models and apply machine learning techniques to identify fraud risks Continuously evaluate and enhance fraud models to maintain detection accuracy Maintain clear documentation of methodology for use across both More ❯

and optimize AI/ML algorithms and tools to enhance national security analysis. • Research and assess quantum computing architectures to identify novel solutions for computational challenges. • Design and evaluate predictive models and neural networks to enhance decision-making processes. • Support the evaluation and deployment of quantum-resistant algorithms and other advanced computing techniques. • Conduct performance benchmarking and scalability analyses More ❯

focus on understanding root causes and driving forward-looking opportunities - Perform statistical tests to establish trends, patterns, seasonality. Use data mining, model building, and other analytical techniques to develop predictive models - Establish relationship between output metrics and drivers to identify and control critical drivers to achieve the desired value of output metric. - Write functional specs for tools and drive More ❯

discoverability, and support Open Science initiatives. Collect, clean, and analyze large datasets of scientific content and related information from various sources, ensuring data quality and integrity. Build and test predictive models and machine learning algorithms for tasks such as entity extraction, workflow automation, and enhancing the understanding of scientific content. Visualize and present findings in a clear, concise, and More ❯

include: Leading the development + delivery of Data Analytics solutions that support strategic decision-making for clients. Managing data solutions projects, including: data strategy, data sourcing, data wrangling, data modelling, data visualisation + data dashboards. Must have strong Data Analytics experience including: SQL and data visualisation tools (PowerBI, Tableau or Looker). Building interactive data dashboards and reports using … Power BI or Tableau. Extracting, cleansing and modelling data from multiple sources to develop clear data insights. Statistical analysis or predictive modelling experience preferred. Working with key stakeholders to scope data requirements + define data solutions. Driving continuous improvement in data analytics processes + data governance policies. Mentoring junior data analysts, data governance + establishing best practices More ❯

of our offer, deepen our knowledge of our audience, and evaluate the impact of our work. You will work collaboratively with the Data & Impact Team to apply advanced data modelling, predictive modelling, and analytical techniques to generate actionable insights. Key Responsibilities: Deliver a high-quality data analytics service: Provide high-quality BAU data reporting and deliver a … specialist audiences. Support leadership: Contribute to sector-leading analytics efforts and identify collaboration opportunities with other leading organisations. Our Ideal Candidate: Experience: Demonstrable experience with large datasets and advanced predictive analysis tools and techniques to produce actionable insights. Proven track record in the production of clear, well written reports, tailored to the business stakeholder requirements. Proficiency in Power BI More ❯

have a keen eye for the continuous improvement of process. As a Senior Pricing Analyst, you will use your advanced analytical skills to: Conducting retail price optimisation analysis/modelling developing customer propensity and Life Time Value (LTV) models to produce the different models and SAS or SQL for data analysis Create innovative data solutions finding new ways to … help make commercial decisions and strategic changes to prices to meet budget requirements. Key Skills and Experience: Previous experience within general insurance pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python More ❯

have a keen eye for the continuous improvement of process. As a Senior Pricing Analyst, you will use your advanced analytical skills to: Conducting retail price optimisation analysis/modelling developing customer propensity and Life Time Value (LTV) models to produce the different models and SAS or SQL for data analysis Create innovative data solutions finding new ways to … help make commercial decisions and strategic changes to prices to meet budget requirements. Key Skills and Experience: Previous experience within general insurance pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python More ❯

of our offer, deepen our knowledge of our audience, and evaluate the impact of our work. You will work collaboratively with the Data & Impact Team to apply advanced data modelling, predictive modelling, and analytical techniques to generate actionable insights. Key Responsibilities: Deliver a high -quality data analytics service: Provide high-quality BAU data reporting and deliver a … analytics efforts and identify collaboration opportunities with other leading organisations. Our Ideal Candidate Candidates will demonstrate our values: Sustainable - Innovative - Proactive Experience: Demonstrable experience with large datasets and advanced predictive analysis tools and techniques to produce actionable insights. Proven track record in the production of clear, well written reports, tailored to the business stakeholder requirements. Proficiency in Power BI More ❯