Job Summary: 

• Work closely with the lead data scientist on the project, the Director of Product Innovation, the developers, and the engineering team.
• Responsible for supporting the development and maintenance of working prototypes powered by data science propositions, ML, and AI.
• Collaborate with the wider team to apply advanced data science concepts in production.
• Contribute to the successful development of features and facilitate understanding of how advanced data science techniques are valuable for products.
• Action prototyping briefs in collaboration with the wider engineering team.
• Propose new product features using knowledge of data science and industry expertise.
• Collaborate with the wider data science team to grow adoption of data science and ML in the organisation.
• Onboard and format new data sets, mostly hosted on BigQuery.
• Collaborate on brainstorming sessions to include new features and approaches.
• Communicate, debug, and escalate any issues with the prototype pipelines.

Skills on Resume:

• Data Science Prototyping (Hard Skills)
• Machine Learning (Hard Skills)
• AI Development (Hard Skills)
• BigQuery Management (Hard Skills)
• Team Collaboration (Soft Skills)
• Feature Ideation (Soft Skills)
• Pipeline Debugging (Hard Skills)
• Technical Communication (Soft Skills)

Job Summary: 

• Design, develop, implement, and evaluate methods, pipelines, and tools for the analysis of EHR data.
• Design, develop, implement, and evaluate machine learning methods for building predictive models.
• Manage research program and ensure all stakeholders are kept up-to-date on progress and outcomes.
• Communicate research goals and results to both technical and non-technical audiences.
• Work effectively in an interdisciplinary environment by engaging a team of clinicians and researchers from health, computer science, statistics, etc.
• Lead and provide technical mentoring to junior postdoctoral fellows and other trainees.
• Contribute to course development in data science and health for graduate students.
• Deliver guest presentations and/or professional workshops on data science topics.
• Respect privacy and ethics around the use of sensitive and privileged data sets.
• Work effectively in a team environment with limited supervision.
• Respect and value diversity in a workplace environment.
• Report to the DSI Scientific Director.

Skills on Resume:

• EHR Data Analysis (Hard Skills)
• Predictive Modeling (Hard Skills)
• Machine Learning (Hard Skills)
• Research Management (Hard Skills)
• Technical Communication (Soft Skills)
• Interdisciplinary Collaboration (Soft Skills)
• Technical Mentoring (Soft Skills)
• Data Ethics Compliance (Hard Skills)

Job Summary: 

• Perform fundamental research work on applying deep learning to different types of data.
• Construct data pipelines and apply data processing, cleansing, and integration.
• Develop, test, and evaluate deep learning algorithms to tackle the underlying problem.
• Assist in model deployment and optimize for performance.
• Develop documentation for developed models.
• Assist in the development of materials and analysis for project proposals and proof of concepts.
• Propose solutions and strategies to business challenges through deep learning.
• Support continuous improvement of team processes and technical practices.

Skills on Resume:

• Deep Learning Research (Hard Skills)
• Data Pipeline Design (Hard Skills)
• Data Processing (Hard Skills)
• Model Development (Hard Skills)
• Model Deployment (Hard Skills)
• Technical Documentation (Hard Skills)
• Business Problem Solving (Soft Skills)
• Process Improvement (Soft Skills)

Job Summary: 

• Participate in structured data labeling initiatives to improve dataset quality.
• Contribute to the development, implementation, and upkeep of algorithms for 2D image processing.
• Support algorithmic solutions for 3D point cloud data analysis and optimization.
• Collaborate on transforming early concepts into functional prototypes.
• Assist in refining prototypes into production-ready solutions.
• Engage throughout the entire product life cycle, from ideation to deployment.
• Work closely with team members across different locations and time zones.
• Take part in technical discussions to share ideas and solve complex problems.
• Collaborate in a creative, interactive, and fast-paced team environment.
• Actively contribute to agile ceremonies such as sprint planning and retrospectives.

Skills on Resume:

• Data Labeling (Hard Skills)
• Image Processing (Hard Skills)
• Point Cloud Analysis (Hard Skills)
• Prototype Development (Hard Skills)
• Production Optimization (Hard Skills)
• Product Lifecycle (Hard Skills)
• Distributed Collaboration (Soft Skills)
• Agile Practices (Soft Skills)

Job Summary: 

• Work on complex and extremely varied data sets from some of the world’s largest organisations to solve real-world problems.
• Develop data science products and solutions for clients and the data science team.
• Write highly optimized code to advance the internal Data Science Toolbox.
• Work in a multi-disciplinary environment with specialists in machine learning, engineering, and design.
• Focus on modelling by working alongside the Data Engineering team.
• Add real-world impact to academic expertise by writing papers and presenting at meetings and conferences.
• Take part in R&D, including video R&D at QuantumBlack, and attend conferences such as NIPS and ICML, and data science retrospectives to share and learn from co-workers.
• Work in one of the most advanced data science teams globally.

Skills on Resume:

• Large-Scale Data (Hard Skills)
• Data Science Solutions (Hard Skills)
• Optimized Coding (Hard Skills)
• Statistical Modeling (Hard Skills)
• Cross-Disciplinary Collaboration (Soft Skills)
• Data Engineering Collaboration (Soft Skills)
• Research Publication (Hard Skills)
• R&D Innovation (Soft Skills)

Job Summary: 

• Support the Senior Data Scientist in delivering innovative technical solutions that meet client requirements.
• Assist in gathering and clarifying technical and business requirements from stakeholders.
• Contribute to data analysis activities to inform solution design.
• Support the development of data-driven solutions across different project stages.
• Participate in testing and evaluating solutions to ensure quality and effectiveness.
• Assist with deploying solutions across the full development lifecycle.
• Learn data engineering techniques to collect raw data from multiple sources.
• Transform raw data into structured inputs suitable for data science models.
• Develop skills in training and evaluating machine learning models using Python or R.
• Support the deployment and monitoring of machine learning models, including low-code and no-code tools.
• Maintain clear and effective written and verbal communication with team members and clients.
• Experiment with new tools and techniques to enhance current and future client solutions.

Skills on Resume:

• Data Analysis (Hard Skills)
• Requirements Gathering (Soft Skills)
• Data Engineering (Hard Skills)
• Data Transformation (Hard Skills)
• Machine Learning (Hard Skills)
• Model Training (Hard Skills)
• Model Deployment (Hard Skills)
• Technical Communication (Soft Skills)

Job Summary: 

• Define and structure data problems to enable effective analysis and solution development.
• Scale analytical approaches to match the complexity and scope of the data challenge.
• Analyze datasets to identify patterns, trends, and actionable insights.
• Manipulate common data formats such as CSV, text files, and JSON.
• Prepare and clean data to ensure accuracy and usability for analysis.
• Convert analytical results into clear and informative data visualizations.
• Develop interactive dashboards using open-source and commercial visualization tools.
• Translate data and visuals into meaningful insights and analytic narratives.
• Communicate findings clearly through data-driven storytelling aligned with research questions.
• Operate effectively in a fast-paced, client-focused environment centered on analysis and reporting.

Skills on Resume:

• Problem Structuring (Hard Skills)
• Scalable Analytics (Hard Skills)
• Data Analysis (Hard Skills)
• Data Cleaning (Hard Skills)
• Data Manipulation (Hard Skills)
• Data Visualization (Hard Skills)
• Dashboard Development (Hard Skills)
• Data Storytelling (Soft Skills)

Job Summary: 

• Develop analytics methods and processes.
• Identify appropriate methods and tools to extract knowledge from data.
• Leverage large volumes of data to answer challenges.
• Prepare data for use in predictive and prescriptive modeling through data cleansing.
• Automate organizational work through scripts for data processing and analytics.
• Develop and apply algorithms and machine learning methods.
• Apply analytic methods and software tools to design and develop analytic programs.
• Perform mathematical modeling.

Skills on Resume:

• Analytics Development (Hard Skills)
• Method Selection (Hard Skills)
• Large-Scale Data (Hard Skills)
• Data Cleansing (Hard Skills)
• Process Automation (Hard Skills)
• Machine Learning (Hard Skills)
• Analytic Programming (Hard Skills)
• Mathematical Modeling (Hard Skills)

Job Summary: 

• Extract data from multiple internal and external sources to support project needs.
• Integrate and join datasets to create a unified and reliable data pool.
• Analyze available business data to understand its structure, quality, and limitations.
• Recommend the most effective modeling strategy based on current data and business goals.
• Contribute to the development of robust and high-performing analytical models.
• Optimize existing models to improve scalability and reusability across projects.
• Ensure models are easily configurable to support different use cases.
• Develop clear explanations to communicate model recommendations to the team.
• Translate technical model outputs into understandable insights for stakeholders.
• Adapt designs and analytical approaches in response to changes in business direction.

Skills on Resume:

• Data Extraction (Hard Skills)
• Data Integration (Hard Skills)
• Business Data Analysis (Hard Skills)
• Model Strategy (Hard Skills)
• Analytical Modeling (Hard Skills)
• Model Optimization (Hard Skills)
• Model Configuration (Hard Skills)
• Stakeholder Communication (Soft Skills)

Job Summary: 

• Work independently and collaboratively within a team on strategic initiatives involving complex data models and solutions.
• Contribute to the design and development of advanced analytical and data-driven solutions.
• Analyze and interpret data to support informed decision-making.
• Extract relevant insights from structured and unstructured data sources.
• Engage with customers to understand evolving requirements and business needs.
• Recommend data-driven solutions based on quantitative and analytical findings.
• Independently compile data from multiple, often inconsistent sources.
• Review and validate disparate datasets to address complex intelligence challenges.
• Apply statistical, mathematical, and analytical techniques to solve complex problems.
• Perform advanced data analysis independently or in collaboration with other analysts and data scientists.
• Provide recommendations for tools and applications that enhance process effectiveness.
• Support continuous improvement by identifying opportunities to increase efficiency and scalability.

Skills on Resume:

• Advanced Analytics (Hard Skills)
• Data Modeling (Hard Skills)
• Data Interpretation (Hard Skills)
• Unstructured Data (Hard Skills)
• Requirements Analysis (Soft Skills)
• Statistical Analysis (Hard Skills)
• Tool Evaluation (Hard Skills)
• Process Improvement (Soft Skills)

Job Summary: 

• Apply structured data science techniques to select, tune, and evaluate algorithms using business-relevant performance metrics.
• Quantify model performance in a way that aligns technical outcomes with business impact.
• Design and execute experiments to test algorithms across both digital and physical environments.
• Validate business hypotheses through controlled experimentation and measurable results.
• Analyze large and complex datasets to uncover insights that drive business value.
• Apply data mining techniques to extract meaningful patterns from high-volume data sources.
• Use exploratory data analysis to identify trends, anomalies, and relationships within data.
• Apply appropriate statistical methods such as clustering, PCA, regression, and significance testing.
• Communicate insights through engaging stories using clear, non-technical language.
• Create compelling visualizations that support decision-making and influence change.
• Confidently extract data from multiple data stores, storage frameworks, and source systems.
• Manipulate and prepare data to ensure it is suitable for advanced analysis.
• Work with descriptive and predictive analytics, including regression models, customer segmentation, and propensity modeling.

Skills on Resume:

• Algorithm Evaluation (Hard Skills)
• Model Performance (Hard Skills)
• Experimental Design (Hard Skills)
• Business Experimentation (Hard Skills)
• Large-Scale Analysis (Hard Skills)
• Data Mining (Hard Skills)
• Exploratory Analysis (Hard Skills)
• Data Storytelling (Soft Skills)

Job Summary: 

• Address complex challenges that require strong data, mathematical, and statistical skills.
• Analyze problems to determine the most appropriate analytical and modeling approaches.
• Convert business questions into clearly defined data science modeling tasks.
• Design and develop models that effectively address business and technical requirements.
• Implement models as reusable and maintainable software components.
• Validate model outputs to ensure accuracy, reliability, and relevance.
• Translate model results into clear and valuable insights for clients.
• Research and apply the latest data science techniques to continuously improve solutions.

Skills on Resume:

• Quantitative Analysis (Hard Skills)
• Analytical Modeling (Hard Skills)
• Problem Translation (Hard Skills)
• Model Development (Hard Skills)
• Model Implementation (Hard Skills)
• Model Validation (Hard Skills)
• Client Insights (Soft Skills)
• Applied Research (Hard Skills)

Job Summary: 

• Collect and consolidate closed data sources for analytical and modeling purposes.
• Process raw data through systematic cleaning and wrangling activities.
• Ensure data quality, consistency, and readiness for downstream use.
• Take responsibility for all client data across the organization.
• Manage data storage, labeling, anonymization, and format standardization.
• Oversee the maintenance and lifecycle of existing and legacy machine learning models.
• Collaborate proactively with team members on ad hoc data analysis tasks.
• Work directly with clients to support one-off analyses, model setup, and reporting needs.
• Assist with configuring and validating machine learning models for specific use cases.
• Support machine learning engineers in research and development initiatives.

Skills on Resume:

• Data Collection (Hard Skills)
• Data Wrangling (Hard Skills)
• Data Quality Control (Hard Skills)
• Data Governance (Hard Skills)
• Data Anonymization (Hard Skills)
• Model Lifecycle (Hard Skills)
• Client Collaboration (Soft Skills)
• Model Validation (Hard Skills)

Job Summary: 

• Take ownership of all finance-related and people-related datasets across the organization.
• Ensure data accuracy, consistency, and reliability for reporting and analysis purposes.
• Collaborate closely with finance and people team leads to analyze product and issue metrics.
• Provide a solid data foundation to support investor reporting.
• Deliver insights that inform strategic management decisions.
• Extract data from enterprise data lakes such as Redshift and BigQuery using SQL.
• Transform and prepare data using Python or R for advanced analysis.
• Create clear and insightful visualizations using Tableau.
• Develop clean, maintainable, and well-structured code following best practices.
• Maintain proper documentation and ensure clean implementations using Git for version control.

Skills on Resume:

• Data Ownership (Hard Skills)
• Data Quality (Hard Skills)
• Business Metrics (Hard Skills)
• Investor Reporting (Hard Skills)
• Strategic Insights (Soft Skills)
• SQL Data Extraction (Hard Skills)
• Data Transformation (Hard Skills)
• Data Visualization (Hard Skills)

Job Summary: 

• Work with data generated from eCommerce transactions and payment card servicing systems.
• Process and prepare transactional data for analytical and reporting purposes.
• Structure data to support reporting within Business Intelligence platforms.
• Ensure datasets are organized to enable accurate and consistent reporting.
• Formulate clear and accurate data requirements during data systematization.
• Identify gaps in available data and define the need for additional data sources.
• Collaborate with internal technical teams to integrate aggregated indicators.
• Support the inclusion of new metrics and attributes into reporting systems.
• Define clear and precise tasks for IT specialists to develop the required data pools.
• Work directly with databases to query and validate reported values.
• Analyze data to ensure correctness and relevance across multiple reports.

Skills on Resume:

• Transactional Data (Hard Skills)
• Data Preparation (Hard Skills)
• BI Reporting (Hard Skills)
• Data Structuring (Hard Skills)
• Requirements Definition (Hard Skills)
• Data Integration (Hard Skills)
• Database Querying (Hard Skills)
• Data Validation (Hard Skills)

Job Summary: 

• Develop new measurement instruments for assessments.
• Decide with the team which tests and assessments will be created.
• Test the reliability and validity of new measurement instruments.
• Stay aware of the latest technical developments and trends in the field.
• Manage normative data.
• Develop algorithms for analyses, visualisations, apps, and reports.
• Design new ways to present data in assessment reports.
• Inspire the team with creative solutions and original ideas.

Skills on Resume:

• Assessment Design (Hard Skills)
• Test Development (Hard Skills)
• Reliability Testing (Hard Skills)
• Validity Analysis (Hard Skills)
• Norm Data Management (Hard Skills)
• Algorithm Development (Hard Skills)
• Data Visualization Design (Hard Skills)
• Creative Ideation (Soft Skills)

Job Summary: 

• Manage and distribute daily, weekly, and monthly reports.
• Assist in the creation of new daily, weekly, and monthly reports.
• Cleanse SQL database data to ensure accuracy.
• Manage office wallboards that provide agents with key information.
• Aid in the design of system developments.
• Analyse, manipulate, and interpret data to provide information that aids company decision-making.
• Identify areas for improvement and report findings to managers.
• Assist in testing of new system developments.

Skills on Resume:

• Report Management (Hard Skills)
• Report Creation (Hard Skills)
• SQL Data Cleansing (Hard Skills)
• Dashboard Management (Hard Skills)
• Data Analysis (Hard Skills)
• Business Insights (Soft Skills)
• System Testing (Hard Skills)

Job Summary: 

• Act as a regional point of contact for value propositions around advanced analytics, machine learning, open source operationalization, modelops, and decisioning.
• Contribute to the promotion of solutions for customers in financial services, telcos, retail, manufacturing, utilities, and other sectors in Southeast Europe.
• Connect technology trends with actual business value for client organizations.
• Build trusted relationships with sales teams and client accounts across Southeast Europe through technology-based discussions.
• Influence sales through domain or business expert credibility by enabling those executing sales cycles or supporting in-country business development efforts.
• Deliver presentations, demos, proposals, and proofs of concept leveraging business acumen.
• Articulate the breadth and value of analytics in relevant sectors and how the offering differentiates in the market.
• Work closely with sales executives and consulting management to validate a go-to-market approach aligned with client needs.
• Contribute to the design and production of sales, customer advisory, and marketing materials, including positioning expertise within conferences, publications, webinars, and social media activities.
• Coordinate internal launch of new services or new value propositions to sales staff.

Skills on Resume:

• Advanced Analytics (Hard Skills)
• Machine Learning (Hard Skills)
• Analytics Evangelism (Soft Skills)
• Client Relationship Building (Soft Skills)
• Sales Enablement (Soft Skills)
• Business Value Translation (Soft Skills)
• Solution Presentation (Soft Skills)
• Go-To-Market Strategy (Hard Skills)

Job Summary: 

• Directly involved in the delivery of projects involving data science and contribute to project planning.
• Lead the technical effort on small-scale projects involving a single team or service.
• Support the project work of other data team members, recognising and promoting opportunities to develop their skills.
• Build and foster a community around the products and services that Digital produces, working to make the organisation a truly data-driven organisation.
• Contribute to the vision for the data programme and demonstrate best practice for applying data science.
• Support and consult other teams across the organisation on data science projects as part of corporate objectives.
• Support analysts across the department participating in the Data Science Accelerator Programme and use 20% of their time learning new skills and trying out new techniques.
• Keep abreast of developments in data science in industry/academia to spot opportunities for applying new data science techniques and tools in government.
• Use data engineering and manipulation techniques to produce or improve data product performance by selecting the most appropriate tools and technologies.
• Understand solutions to build effective data management systems to ingest data from a variety of external sources, cleanse and transform data for analysis, and enable sharing across many platforms.
• Use a range of data sources, analytical tools, and techniques throughout the life cycle to develop and deploy robust data science solutions into the business.

Skills on Resume:

• Data Science Delivery (Hard Skills)
• Project Leadership (Soft Skills)
• Technical Mentoring (Soft Skills)
• Data Strategy (Hard Skills)
• Data Consulting (Soft Skills)
• Applied Research (Hard Skills)
• Data Engineering (Hard Skills)
• End-to-End Solutions (Hard Skills)

Job Summary: 

• Conduct data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and use scientific techniques to correlate data into graphical, written, visual, and verbal narrative products to enable more informed analytic decisions.
• Retrieve information proactively from various sources, analyze it for a better understanding of the data set, and build AI tools to automate specific processes.
• Create ML-based tools or processes such as recommendation engines and automated lead scoring systems.
• Perform statistical analysis, apply data mining techniques, and build high-quality prediction systems.
• Use data visualization and graphical applications, including Microsoft Office Power BI and Tableau, major data science languages such as R and Python, and manage and merge disparate data sources through R, Python, or SQL.
• Apply statistical analysis and data mining algorithms.
• Work with large data multi-INT analytics, machine learning, and automated predictive analytics.
• Research and develop statistical learning models for data analysis.
• Collaborate with all source analysts to understand needs and devise possible solutions, and communicate results and ideas to key decision makers.
• Implement new statistical or mathematical methodologies for specific models or analyses.
• Optimize joint development efforts through appropriate database use and project design.
• Apply academic social science theory in computer models.

Skills on Resume:

• Advanced Analytics (Hard Skills)
• Data Engineering (Hard Skills)
• Machine Learning (Hard Skills)
• Predictive Modeling (Hard Skills)
• Statistical Analysis (Hard Skills)
• Data Visualization (Hard Skills)
• AI Automation (Hard Skills)
• Stakeholder Communication (Soft Skills)