Data science roles bridge statistics, programming, and business intelligence. Demand is strong across all sectors (from fintech to e-commerce), with Python, SQL, and cloud data platforms (Snowflake, BigQuery, dbt) as the core stack.
Version 1 has several strategic technology partners including Microsoft, AWS, Oracle, Red Hat, OutSystems and Snowflake. Typically The Role Will Involve The Following Translating Business requirements to technical…
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Version 1 has several strategic technology partners including Microsoft, AWS, Oracle, Red Hat, OutSystems and Snowflake. Typically The Role Will Involve The Following Translating Business requirements to technical solutions and the production of specifications, Designing and implementing business intelligence & modern data analytics platform technical solutions, Data architecture design and implementation Data modelling, ETL, data integration and data migration ...
You will use data and analysis to identify and solve product development's biggest challenges. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics:…
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You will use data and analysis to identify and solve product development's biggest challenges. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics: You will guide teams using data and insights.
You will use data and analysis to identify and solve product development's biggest challenges. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics:…
Read full description
You will use data and analysis to identify and solve product development's biggest challenges. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics: You will guide teams using data and insights.
You will use data and analysis to identify and solve product development's biggest challenges. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics:…
Read full description
You will use data and analysis to identify and solve product development's biggest challenges. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics: You will guide teams using data and insights.
You will use data and analysis to identify and solve product development's biggest challenges. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics:…
Read full description
You will use data and analysis to identify and solve product development's biggest challenges. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics: You will guide teams using data and insights.
You will use data and analysis to identify and solve product development's biggest challenges. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics:…
Read full description
You will use data and analysis to identify and solve product development's biggest challenges. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics: You will guide teams using data and insights.
You will use data and analysis to identify and solve product development's biggest challenges. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics:…
Read full description
You will use data and analysis to identify and solve product development's biggest challenges. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.Analytics: You will guide teams using data and insights.
We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.About The RoleAs a Data Scientist…
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We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.About The RoleAs a Data Scientist focusing on Quantitative Trading NLP, you will leverage natural language understanding techniques such assentiment analysis, intent recognition, and named-entity extractionon financial news, social media, and other text streams to develop and refine algorithmic trading strategies.You’ll design and implement machine-learning models in Python, apply advanced mathematical and time-series analysis to uncover predictive signals, and rigorously backtest and optimize strategies to maximize returns while managing risk. Collaboration and clear communication across data science and trading teams are key to iteratively improving model performance and driving data-informed investment decisions.Responsibilities:Research and develop quantitative trading strategies using NLU methods such as sentiment analysis, intent recognition, named-entity extraction on financial news, social media, and other text sourcesDesign and build machine-learning models to uncover predictive trading signals and perform exploratory data analysis on large, complex datasetsApply mathematical techniques (probability, statistics, time-series analysis) to refine and strengthen trading modelsRigorously backtest strategies against historical data and iteratively optimise models to boost performance and curb riskRequirements:At least 2 years of relevant experience in data science, machine learning, or natural language processingBachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Financial Engineering, or a related disciplineStrong mathematical foundation: probability, statistics, linear algebra, time-series analysis, and familiarity with ML frameworks (Scikit-learn, TensorFlow, PyTorch)Solid grasp of NL...
Work Schedule Standard (Mon-Fri) Environmental Conditions Office Job Description Company Overview Thermo Fisher Scientific Inc. Core Responsibilities Design, develop, and maintain backend services and AI-enabled…
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Work Schedule Standard (Mon-Fri) Environmental Conditions Office Job Description Company Overview Thermo Fisher Scientific Inc. Core Responsibilities Design, develop, and maintain backend services and AI-enabled applications that support scientific and bioprocessing workflows.
Newsweek Recognizes Sedgwick as Americas Greatest Workplaces National Top Companies Certified as a Great Place to Work Fortune Best Workplaces in Financial Services & Insurance Data Scientist (REMOTE) Data Scientist…
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Newsweek Recognizes Sedgwick as Americas Greatest Workplaces National Top Companies Certified as a Great Place to Work Fortune Best Workplaces in Financial Services & Insurance Data Scientist (REMOTE) Data Scientist (Remote) PRIMARY PURPOSE OF THE ROLE: To develop and manage predictive modeling assignments through completion; to communicate results; to make recommendations to management; and to ensure model ownership, implementation, and monitoring; to spot trends and to gain maximum insight that can give the company a competitive advantage. Essential Responsiblities May Include Execute data science projects as identified by Sr Data Scientists, leadership, and stakeholders Help to build, prototype, and deploy machine learning models in sandbox and production environments Produce reports to communicate metrics and outcomes of stakeholder interest Assist with developing and maintaining end-to-end ETL data pipelines Work to explore new internal data sources and their utility within projects Communicate modeling challenges, findings, and outcomes to stakeholders Qualifications Insurance claims knowledge preferred Minimum one year of predictive modeling, data science, and analysis experience with solid background in the using data visualization tools and libraries and data exploration, data wrangling, and feature engineering Experience writing Python or R code, and notebook environments Knowledge of common unsupervised/supervised ML techniques TAKING CAR...
Data Scientist – Personalization & Customer Analytics (Mid / Senior) 📍 Remote (Europe) Eligible to work in EU / Europe ✈️ 1–2 weeks per year in NYC (optional) At F. We are expanding our Data Strategy & Analytics team…
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Data Scientist – Personalization & Customer Analytics (Mid / Senior) 📍 Remote (Europe) Eligible to work in EU / Europe ✈️ 1–2 weeks per year in NYC (optional) At F. We are expanding our Data Strategy & Analytics team and are looking for business-oriented Data Scientists (mid-level and senior) who enjoy working close to commercial teams, exploring data, building practical machine-learning models, and translating insights into real impact.
Investigate data patterns to support strategic business decisions. Show less…
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Investigate data patterns to support strategic business decisions. Show less [{"type":"people_also_viewed","href":"https://uk..com/jobs/view/software-engineer-ii-site-reliability-engineering-at-hackajob-4360951890","jobId":"4360951890","label":"Software Engineer II - Site Reliability Engineering"},{"type":"people_also_viewed","href":"https://uk..com/jobs/view/data-analyst-at-walker-group-4369132753","jobId":"4369132753","label":"Data Analyst"},{"type":"people_also_viewed","href":"https://uk..com/jobs/view/application-engineer-at-emerson-4345101877","jobId":"434...
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Yes. Remote-friendly AI and ML roles in the EU have grown over 30% year-on-year. Germany, France, the Netherlands, and Spain lead in volume. Use the AI and EU filters together to surface them quickly, and check the salary estimate badge to ensure the range meets your expectations.
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AI and ML engineer roles currently command the highest median salaries on Catalitium, around $150k–$200k USD in the US and EUR 100k–EUR 160k in Europe. Principal and Staff Engineer roles come close, followed by senior full-stack and cloud infrastructure engineers. Use the >100k filter to see only high-compensation listings.
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Which European cities pay the most for tech?
Zurich and Geneva (Switzerland) consistently top European tech salaries, followed by London, Amsterdam, Berlin, Paris, and Stockholm. Swiss salaries are typically quoted in CHF and translate to EUR 100k–160k for mid-senior roles. London follows at GBP 70k–110k. Berlin and Amsterdam are competitive at EUR 70k–100k for comparable experience levels.
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Which tech stacks are most in demand?
Across Catalitium tech listings, Python, TypeScript/JavaScript, Go, Java, and cloud platforms (AWS, GCP, Azure, Kubernetes) recur most often; AI and data roles add PyTorch, TensorFlow, and LLM tooling. Title and AI summary chips reflect the employer's stated stack.
Which Swiss cities pay the most for software roles?
Zurich and Geneva typically lead Switzerland for software, data, and platform engineering compensation; smaller hubs follow at a discount. Swiss ranges often sit above neighbouring EU markets for comparable seniority—check Est. salary on each card when you filter by Switzerland.
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