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.
This role will need a deep understanding of data, strong communication skills, and solid knowledge of experimentation. Excellent analytical skills, with experience extracting user behavior insights from large datasets.
This role will need a deep understanding of data, strong communication skills, and solid knowledge of experimentation. Excellent analytical skills, with experience extracting user behavior insights from large datasets.
Support the implementation of data-driven marketing strategies, including segmentation and personalization. Experience with data visualization tools like Tableau, Power BI, or Google Data Studio.
Job Description: Type of Requisition: Regular Clearance Level Must Currently Possess: None Clearance Level Must Be Able To Obtain: Top Secret Public Trust/Other Required: None Job Family: Intelligence Operations and…
Read full description
Job Description: Type of Requisition: Regular Clearance Level Must Currently Possess: None Clearance Level Must Be Able To Obtain: Top Secret Public Trust/Other Required: None Job Family: Intelligence Operations and Analysis Skills: Job Qualifications: Collaborating, Data Libraries, Evaluate Information, Programming Languages Certifications: None Experience: 2 + years of related experience US Citizenship Required: Yes Job Description: INTELLIGENCE ANALYST Contribute to the strategic direction of the business and support impactful mission outcomes as an Intelligence Analyst at GDIT. The Intelligence Analyst must have: Education: Bachelor of Arts/Bachelor of Science Experience: 2+ years of related experience or Masters Degree Technical skills: Knowledge of various applicable programming languages, technologies, and libraries Security clearance level: Top Secret US citizenship required Role requirements: The primary place of performance will be the Olney Support Center and NSWC Carderock.
Qualifications 5+ years of experience in Data Analytics and SQL. Key Skills: Data Science, SQL, Python, PowerBI, Data Visualization, Player Insights, Statistical Analysis, Databricks.
Now Brewing – Data Scientist! As a data scientist, you will… Conduct Exploratory Data Analysis - Analyze large-scale datasets through data wrangling, feature engineering, and statistical exploration.
Data Scientist Classified AI Predictive Analytics & Military Readiness DC Area The Opportunity This team builds custom AI systems for defence and national security, tackling complex, high-stakes problems such as…
Read full description
Data Scientist Classified AI Predictive Analytics & Military Readiness DC Area The Opportunity This team builds custom AI systems for defence and national security, tackling complex, high-stakes problems such as predictive maintenance, logistics optimisation, and readiness modelling across personnel, equipment, and supply chains. Location, clearance & comp DC area, mostly remote with onsite requirements Must be eligible for secure/classified work Interview process: 30-min intro → take-home → technical interview → final panel Show less
[Industry: Accounting, IT Services and IT Consulting, and Business Consulting and Services | Type: Full-time | Level: Not Applicable] Our Deloitte Strategy & Transactions team helps guide clients through their most…
Read full description
[Industry: Accounting, IT Services and IT Consulting, and Business Consulting and Services | Type: Full-time | Level: Not Applicable] Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformatio
Troubleshoot and resolve issues related to data models, data pipelines, and reporting. Experience with data governance, compliance, and best practices.
Data Engineering Manager, Analytics Responsibilities: Drive the mission and strategy for Business Intelligence (BI) and Data Warehousing across a product vertical Build and lead a high-quality BI and Data Warehousing…
Read full description
Data Engineering Manager, Analytics Responsibilities: Drive the mission and strategy for Business Intelligence (BI) and Data Warehousing across a product vertical Build and lead a high-quality BI and Data Warehousing team, designing it to scale Develop cross-functional relationships with stakeholders to understand data needs and deliver on those needs Manage data warehouse plans, drive data quality, and ensure operational efficiency Design, build, and launch new data models and pipelines in production Deliver high-impact dashboards and data visualizations Define and manage Service Level Agreements (SLAs) for all data sets and processes running in production Drive efficiency and speed, project management leadership, and a vision for how BI can proactively improve companies Minimum Qualifications: A minimum of 4 years of work experience (2+ years with a Ph.D.) in applied analytics, including a minimum of 2 years of experience managing analytics teams 8+ years of experience in BI and Data Warehousing 2+ years of experience managing people with experience scaling and managing 3+ person teams Bachelor of Arts/Bachelor of Science in Computer Science, Math, Physics, or other technical fields Experience initiating and completing BI, data warehousing and/or analytical projects with minimal guidance Experience communicating results of analysis to executive leadership Project management experience Data architecture experience Experience with data querying languages (e.g. SQL) and development experience in at least one object-oriented language (Python, Java, etc.) Experience working closely on cross-functional teams, including Data Engineering, Data Science, Software Engineering, and Product Management Preferred Qualifications: Experience working closely on cross-functional teams, including Data Engineering, Data Science, Software Engineering, and Product Management Experience with Big Data, Hadoop, and Data visualization...
We are looking for a Data Engineer in Leo's Global Planning team to build enterprise-grade data infrastructure and data assets that will support Leo's Demand Science & Forecasting models and capacity planning &…
Read full description
We are looking for a Data Engineer in Leo's Global Planning team to build enterprise-grade data infrastructure and data assets that will support Leo's Demand Science & Forecasting models and capacity planning & simulation systems. Key job responsibilities In This Role, You Will Develop Leo data products, infrastructure and ETL pipelines to ingest, parse and transform Geospatial datasets from external & internal APIs using AWS big data technologies (Glue, S3, Redshift, MWAA, EMR, Data Zone, Lambda, etc.) Work alongside Data Scientists, Applied Scientists, Software Engineers and Simulation Engineers to develop appropriate data assets for statistical modeling, system integration and capacity simulations Improve existing solutions and come up with next generation Leo's Data Architecture to improve scale, quality and performance Implement data governance best practices to ensure data accuracy, consistency, and compliance with security and privacy regulations.
We are looking for a Data Engineer in Leo's Global Planning team to build enterprise-grade data infrastructure and data assets that will support Leo's Demand Science & Forecasting models and capacity planning &…
Read full description
We are looking for a Data Engineer in Leo's Global Planning team to build enterprise-grade data infrastructure and data assets that will support Leo's Demand Science & Forecasting models and capacity planning & simulation systems. Key job responsibilities In This Role, You Will Develop Leo data products, infrastructure and ETL pipelines to ingest, parse and transform Geospatial datasets from external & internal APIs using AWS big data technologies (Glue, S3, Redshift, MWAA, EMR, Data Zone, Lambda, etc.) Work alongside Data Scientists, Applied Scientists, Software Engineers and Simulation Engineers to develop appropriate data assets for statistical modeling, system integration and capacity simulations Improve existing solutions and come up with next generation Leo's Data Architecture to improve scale, quality and performance Implement data governance best practices to ensure data accuracy, consistency, and compliance with security and privacy regulations.
Salary tags blend employer provided ranges with Catalitium estimates. We mark ranges with Est. labels, note any missing data, and never inflate compensation to boost clicks.
Currency harmonized to USD/EUR/GBP/CHF to avoid surprises.
Outliers are reviewed manually before they appear on a card.
Sponsored employers follow the same disclosure and pay rules.
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.
How fresh are the job postings?
Listings are refreshed continuously from employer feeds and normalised daily. Each card shows a posted date pill so you can see exactly how old a listing is. Jobs posted within the last 7 days receive a green New badge. Listings older than 30 days receive a May be filled warning.
Do roles include salary estimates?
Yes. Most listings show an Est. salary pill derived from Catalitium's location-based salary database, blended with any employer-disclosed range. Senior and lead roles receive an automatic seniority uplift. If a salary range is genuinely unknown we leave the field blank rather than show a misleading estimate.
What is a ghost job and how do I spot one?
A ghost job is a listing that has been live for 30+ days and is likely already filled, on hold, or was never a real opening. Research suggests up to 40% of active listings at any time are ghost jobs. Catalitium flags every listing older than 30 days with a triangle May be filled badge so you can prioritise your energy on fresh openings.
What are the highest-paying tech roles right now?
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.
How do I negotiate a higher salary offer?
Reference Catalitium's salary data when negotiating: show the employer the market range for your role and region. Studies show engineers who negotiate receive 10–20% more than the initial offer on average. If base salary is fixed, push on equity, signing bonus, remote allowance, and learning budget. See our Salary Negotiation Guide in the Resources section.
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.
Can I track my job applications on Catalitium?
Yes. Our free Application Tracker lets you move roles through a Kanban pipeline: Applied, Phone Screen, Interview, Offer, and Closed. It requires no account and stores everything privately in your browser. Hit the Track button on any job card to add it. You can also export your full pipeline as a CSV.
How does Catalitium differ from LinkedIn Jobs?
LinkedIn optimises for engagement and premium upgrades. Catalitium is built exclusively for tech candidates who want signal over noise: every listing shows salary estimates, ghost jobs are flagged, AI-powered summaries save you time reading descriptions, and the application tracker replaces the black-hole Easy Apply experience. No premium paywall, no recruiter spam.
Can I filter to remote-only jobs?
Yes. Choose Remote in the location/country field or tap a Remote shortcut chip. Results are limited to roles that advertise remote or hybrid where the listing text supports it, and remote-friendly rows show a Remote badge.
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.
Save this search and get a weekly digest of top matches.
Includes salary signal. No spam.
