1 to 25 of 45 Exploratory Analysis Jobs

Develop and maintain data-driven solutions that improve business decision making Participate in the full analytics lifecycle, including data acquisition, exploratory analysis, model development, deployment support, monitoring, and communication of results Collaborate with the Managing Data Scientist, team members, cross-functional partners, and business stakeholders Apply statistical, machine … hands-on experience using Python to solve analytical, data science, machine learning, or data engineering problems Foundational understanding of statistics, machine learning, and data analysis techniques Experience applying statistical, machine learning, and data analysis concepts to real-world business, academic, or personal projects Strong problem-solving, communication ...

full consumer lifecycle — from acquisition and activation through engagement, retention, churn and reactivation.Identify opportunities to improve conversion, customer value and sustainable growth using funnel analysis, cohort analysis, segmentation and behavioural analytics.Collaborate closely with Product Managers, Designers, Engineers and Data teams to ensure decisions are grounded in robust analysis … trade-offs exist.Support decisions that improve key business outcomes, such as activation, conversion, repeat usage, retention, churn, customer lifetime value and revenue-related metrics.Conduct exploratory analysis to answer product and business questions, translating complex data into clear, commercially relevant recommendations.Define, monitor and communicate core SumUp Consumer KPIs, covering ...

fraudulent? What will demand look like next quarter? — and answer it with data. The work spans the full pipeline: sourcing and cleaning data, exploratory analysis, feature engineering, training and validating models (regression, tree ensembles, neural networks), then communicating results to non-technical stakeholders and, increasingly, shipping those models … fraudulent? What will demand look like next quarter? — and answer it with data. The work spans the full pipeline: sourcing and cleaning data, exploratory analysis, feature engineering, training and validating models (regression, tree ensembles, neural networks), then communicating results to non-technical stakeholders and, increasingly, shipping those models ...

models for forecasting, classification, recommendation, optimisation, clustering and anomaly detection. Apply statistical and machine learning techniques to analyse structured and semi-structured datasets. Perform exploratory data analysis, feature engineering, model training, validation and model evaluation. Compare model approaches, select appropriate metrics and explain technical trade-offs clearly. Build … bring: Required: 3-5 years of commercial experience in Data Science, Machine Learning or Advanced Analytics roles. Strong hands-on Python experience for data analysis, feature engineering and model development. Strong SQL skills and experience working with complex or sizeable datasets. Solid theoretical and practical understanding of supervised learning ...

Responsibilities Engage directly with business stakeholders, report owners, and customers to gather, analyze, and refine business requirements. Translate business requirements into SQL-based data analysis, reports, dashboards, and actionable insights. Perform root cause analysis and investigate data quality, reporting, and operational issues. Develop ad hoc analyses, prototypes, mock … Skills Strong expertise in SQL with the ability to write complex queries, troubleshoot issues, and perform advanced data analysis. Proficiency in Python for data analysis, data profiling, exploratory analysis, and rapid prototyping. Solid understanding of data modeling concepts , relational databases, and analytical data structures. Experience working with ...

capability and data gaps, support technical trade studies, and evaluate analytic or AI/ML-enabled capabilities. As appropriate, the candidate will develop repeatable analysis workflows using Python, SQL, Jupyter, statistical methods, data visualization, and machine learning techniques to inform architecture and mission-engineering decisions. This role requires close … metadata, data lineage, and provenance needed to support integration and analytics. Acquire, clean, transform, explore, and analyze structured and unstructured data to support engineering analysis, mission assessment, capability evaluation, and operational decision support. Apply statistical analysis, feature engineering, anomaly detection, classification, clustering, forecasting, or other machine learning techniques ...

development decisions in close collaboration with internal and external partners.Job DescriptionMajor accountabilities:You will contribute to planning, execution, interpretation, validation and communication of innovative exploratory analyses and algorithms, to facilitate internal decision makingYou will provide technical expertise in data science and (predictive) machine learning/AI to identify opportunities … influencing internal decision making as well as discussions on white papers/regulatory policy.You will perform hands-on analysis of integrated data from clinical trials and the real world to generate fit-for-purpose evidence that is applied to decision making in drug development programs.Translate business questions into analytical ...

Python (4) Geospatial intelligence software (5) APIs from commercial/open-source providers.The data scientist will be expected to conduct exploratory analysis of datasets to address a range of client problem sets.Open-Source Intelligence and data exploitationThe data scientist is not expected to be trained/experienced … with hands-on experience developing models that solve practical problems and deliver measurable impact.You are comfortable working across the full machine learning lifecycle – from exploratory data analysis and model prototyping to production deployment, integration, and ongoing monitoring.You are proficient in Python and its data/ML ecosystem (e.g. ...

Python (4) Geospatial intelligence software (5) APIs from commercial/open-source providers. The data scientist will be expected to conduct exploratory analysis of datasets to address a range of client problem sets. Open-Source Intelligence and data exploitation The data scientist is not expected to be trained … hands-on experience developing models that solve practical problems and deliver measurable impact. You are comfortable working across the full machine learning lifecycle from exploratory data analysis and model prototyping to production deployment, integration, and ongoing monitoring. You are proficient in Python and its data/ML ecosystem ...

close collaboration with internal and external partners. About the Role Major accountabilities: You 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 integrated data from clinical trials and the real world to generate fit-for-purpose evidence that is applied to decision making in drug development programs. Translate ...

role for someone who enjoys variety and has a critical eye for finding the right solution for the problem. Sometimes this may be exploratory analysis, a dashboard or a set of clearly defined metrics; in other cases, it may involve forecasting, statistical modelling, machine learning or building/… sharing approaches, reusable methods and good practice About you To be successful in this role you’ll need: Essential skills: Experience applying data and analysis to real-world business, engineering or operational problems. Strong analytical problem-solving skills, with the ability to take an initially ambiguous question and determine ...

role for someone who enjoys variety and has a critical eye for finding the right solution for the problem. Sometimes this may be exploratory analysis, a dashboard or a set of clearly defined metrics; in other cases, it may involve forecasting, statistical modelling, machine learning or building/… sharing approaches, reusable methods and good practice About you To be successful in this role you’ll need: Essential skills: Experience applying data and analysis to real-world business, engineering or operational problems. Strong analytical problem-solving skills, with the ability to take an initially ambiguous question and determine ...

role for someone who enjoys variety and has a critical eye for finding the right solution for the problem. Sometimes this may be exploratory analysis, a dashboard or a set of clearly defined metrics; in other cases, it may involve forecasting, statistical modelling, machine learning or building/… sharing approaches, reusable methods and good practice About you To be successful in this role you’ll need: Essential skills: Experience applying data and analysis to real-world business, engineering or operational problems. Strong analytical problem‐solving skills, with the ability to take an initially ambiguous question and determine ...

explore, analyze, and communicate insights from clinical trial data. This role combines clinical trial expertise, statistical thinking, and modern R programming to support exploratory analyses, facilitate scientific discussions, and generate actional insights for study teams.The successful candidate will work closely with statisticians, clinicians, and R application developers to identify … meaningful analytical questions, prepare clinical datasets, generate interactive visualizations, and drive improvements to the DIG analytical platform.Key Responsibilities- Perform exploratory analyses of clinical trial data using interactive R/Shiny applications.- Prepare, integrate, and quality-check clinical datasets for downstream exploratory analyses.- Identify trends, safety signals, efficacy patterns ...

making. Working closely with the Managing Data Scientist and cross-functional partners, the individual will participate in the full analytics lifecycle, including data acquisition, exploratory analysis, model development, deployment support, monitoring, and communication of results. The role is expected to apply statistical, machine learning, and emerging AI techniques … hands-on experience using Python to solve analytical, data science, machine learning, or data engineering problems. Foundational understanding of statistics, machine learning, and data analysis techniques, with experience applying those concepts to real-world business, academic, or personal projects. Strong problem-solving, communication, and collaboration skills. Ability to independently ...

evolution of data architectures by contributing analytical requirements and feedback.Communicate analytical findings clearly to non-technical stakeholders to inform strategy and operational improvements.Conduct exploratory analysis and limited prototyping to evaluate emerging data techniques relevant to training analytics.Ensure analytics processes comply with security, governance, and regulatory requirements.Author and maintain … data security principles, governance frameworks, and MOD compliance standards.Strong SQL skills for querying and manipulating structured datasets.Proficiency in Python or R for statistical analysis, data wrangling, and automation.Experience building dashboards and visualisations using Power BI, Tableau, or equivalent BI tools.Advanced Excel skills for analytical modelling and reporting.Familiarity with cloud ...

data architectures by contributing analytical requirements and feedback. Communicate analytical findings clearly to non-technical stakeholders to inform strategy and operational improvements. Conduct exploratory analysis and limited prototyping to evaluate emerging data techniques relevant to training analytics. Ensure analytics processes comply with security, governance, and regulatory requirements. Author … security principles, governance frameworks, and MOD compliance standards. Strong SQL skills for querying and manipulating structured datasets. Proficiency in Python or R for statistical analysis, data wrangling, and automation. Experience building dashboards and visualisations using Power BI, Tableau, or equivalent BI tools. Advanced Excel skills for analytical modelling ...

researchers to build a holistic understanding of our customers, our products and our business.You’ll influence our product roadmap and product strategy through experimentation, exploratory analysis and quantitative researchYou’ll build and automate actionable models and dashboardsYou’ll craft data stories and share your findings and recommendations across … drive evidence-based decisionsExcellent SQL skills and experience of applying analytical and statistical approaches to problem solvingProven track record of initiating and delivering actionable analysis and insights that drives tangible impact with minimal supervisionExcellent communication skills (technical and non-technical) and a focus on driving impactStrong growth mindset ...

product researchers to build a holistic understanding of our customers, our products and our business.You’ll influence our product roadmap and product strategy through exploratory analysis and quantitative researchIncreasingly, you will also:Use AI-assisted tools (e.g. Claude Code, Cursor) to accelerate analysis, coding and insight generationIdentify … with product teamsProven track record of delivering actionable insights that drive measurable impact with minimal supervisionStrong product intuition, business acumen and ability to connect analysis to strategyExcellent communication skills (technical and non-technical), with a focus on driving decisions and outcomesStrong ownership, curiosity and growth mindsetExperience with a scientific ...

sources independently to build datasets suited for modelling and in-depth analysis. Design and execute measurement frameworks — including A/B testing, causal impact analysis, and multivariate methods — selecting the appropriate technique based on the business question and clearly communicating trade-offs. Build, evaluate, and iterate on statistical models … scale Proficient understanding of statistical concepts including regression, ANOVA, probability, and frequentist vs. Bayesian approaches, with the ability to distinguish statistically significant results from exploratory analysis Experience applying a range of modelling techniques (e.g. linear and logistic regression, clustering) and iterating on models to improve accuracy and business ...

credit risk scores, predictive models, and AI-driven commercial data products on modern cloud infrastructure. The Data Scientist will: Independently prepare complex datasets, run exploratory analysis, and build predictive models, risk scorecards, and decisioning tools Drive commercial product innovation - identify market gaps, prototype algorithms, take concepts to market ...

with other internal and external data sources in Google BigQuery and Power BI to support Canon’s ITCG marketing, ecommerce and CRM team initiatives.Perform exploratory analysis using Python/R and SQL to uncover trends, anomalies, and business opportunities in ITCG digital marketing and sales data and present ...

deployment and monitoring. Technical depth: Apply strong statistical modelling, ML, and (where relevant) NLP/LLM techniques to solve real business problems, not just exploratory analysis. Experimentation and measurement: Design and run experiments (A/B testing, causal inference) to validate impact and guide decision making. Cross-functional delivery ...

best-action modelling to generate insight and improve customer decisions.Write production-quality code and review the work of data scientists and AI engineers, including analysis, model design, code, prompts and data pipelines.Establish robust approaches to data preparation, experimentation, validation and performance measurement, ensuring outputs are reliable, actionable and aligned … Python and review and improve the code, analytical methods, model designs, prompts and pipelines produced by others.Data science and analytics fundamentals. Strong understanding of exploratory analysis, statistical methods, experimentation and machine learning, including experience developing, evaluating and deploying models. You know when traditional analytics or machine learning ...

internal and external data sources. Engineering new features and rating factors to enhance existing pricing algorithms. Managing the full machine learning lifecycle, from exploratory analysis through to deployment, monitoring, and model refresh activities. Working closely with Data Scientists, Data Engineers, Analysts, and business stakeholders to translate challenges into ...