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Cloud Platform

Cloud platform developed by Corplan helps navigate in the world of trading and investments in a most friendly way. Users can follow several stocks, specify signals, and apply models to generate the best scenario.

  • Compatible with all major operating systems.
  • Customizable application interface with various settings.
  • Preset parameters for machine learning engine.
  • Stock exchange integration for real-time stock quotes.
  • Filtering and screening lists of stocks for better results.

Cloud platform by Corplan offers functionality that encompasses all typical trading actions and provide value added services based on machine learning engine and data enhancement.

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Mobile App

The Mobile App offers excellent features for those who prefer trading with use of mobile devices, anytime, anywhere. Corplan enhances trading experience with state-of-the-art mobile technologies.

  • iOS and Android versions.
  • Adaptive screens and graphs.
  • Good Internet connectivity.
  • Different skins applicable.
  • Easy-to-use interface.

Corplan continues development and improvement of functionality in response to users requirements and feedback that we collect from early adopters.

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On-premise Solution

On-premise solution provide the core functionality of Corplan. It offers intelligent approach to trading decisions, suggests traders the best opportunities for profit-making buy/sell trades.

  • Extended financial models based on big statistical data.
  • Different machine learning scenarios.
  • Cross-functional features for setting dependenicies.
  • Regular and timely alerts on best conditions for buy/sell.
  • Extended reporting to analyze the most successful data models.

Machine learning includes the 'learning' kernel that is capable to process multi-dimensional, statistical data in seconds. The excellent oppotunity is to learn with each new trade.

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Cloud Platform

Cloud platform developed by Corplan helps navigate in the world of trading and investments in a most friendly way.

mobile application

Corplan offers excellent features for those who prefer trading with the use of mobile devices, anytime, anywhere.

On-premise Solution

On-premise Solution employs self-learning algorithms which makes it better and more accurate with each new trade.

More services

Along with basic functionality Corplan offers extended features and user customization for better trading opportunities.
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Corplan continues development and evolution all the time introducing newer features to satisfy extended demand from traders and investors.

Extended Corplan solution offers more signals and patterns to analyze stock quotes and make notifications. Traders can select from the list of typical trading signals that indicate trends in stock charts.

Corplan offers real-time user notifications based on pre-set system events or criteria. Notifications are sent to mobile devices, email, or in text messages.

On-premise Solution contains 'self-learning' kernel that constantly evolves and improves. You can also apply statistical historical data to make even better decisions.

Corplan offers connection to diverse stock exchanges enabling users to trade across markets. You can also apply proven trading models from one stock to another similar stock.

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We are hiring

"Shazam for trading", which recognizes market signals, purifies them and informs the trader on the most appropriate moment to buy or sell.
Trading Analysts are responsible for our assumption management models. In order to regularly maintain and enhance these assumption models, a large part of the role will consist of the development and production of regularly scheduled and ad hoc data extracts and reports. This position will serve as a subject-matter-expert in understanding the structure on how our assumptions and execution strategies impact our profit margins, cash flows, and servicing risks.


  • Assumptions management & modeling.
  • Maximize execution for the company.
  • Minimize monetary risk to the company.
  • MSR modeling & valuation.
  • Prepare theoretical hedging and/or trading scenarios using historical data to characterize future behavior.
  • Ensure efficiency of reporting across business units; continually review quality and data integrity for presentations.
  • Collect, process, and analyze historical data derived from disaggregated sources.
  • Broker Dealer, Correspondent, and Vendor Relationship Management.
  • Necessary Skills : A strong work ethic, quantitative and analytical decision-making skills, and strong interpersonal communication skills.


  • Minimum of 2 years of in-depth Excel, Access, and/or SQL experience, preferred.
  • Skilled in relational database technologies and data modeling tools, such as Access, SQL Server, MySQL, or Oracle is preferred.
  • Experience in presentation tools, such as PowerPoint, Word, Visio, etc.
  • Ability to synthesize data to identify trends and hypothesize scenarios.
  • Strong business acumen, with the ability to translate and present quantitative information in a professional format.
  • Proficient in basic computer technologies, appropriate for an internet-based company.
The Data Science Engineer plays a pivotal role in building the future digital competitive advantage - to transform capabilities for customers, to drive new and protect existing revenue and to drive a low cost operating model. This is an exciting opportunity to join the directorate, and work with a group of pathfinders.


  • Act as a data sourcing for analytics and modelling within the Enterprise data lake. Keeping up to speed with wider capabilities and data they become available.
  • Act as a partner to model developers/implementation to provide access to high-quality data for model build, insight and automation.
  • Automation and monitoring of high-quality data layers for wider consumption within Enterprise data lake and modelling community.
  • Influencing upstream data collection strategy for a wider integration eg. web tagging, server side data collection.
  • Delivering a feedback loop for model performance monitoring.


  • Optimisation performance - familiarity with partitioning, bucketing, indexing etc. Ability to demonstrate accurate data manipulation.
  • Hadoop - Broad knowledge of Hadoop eco-system. i.e. kafka, storm, spark, oozie etc.
  • Data modelling - Knowledge of data modelling within an Enterprise data warehouse / Big Data environment . i.e. denomalised views, star schemas, third-normal form, OLAP cubes etc.
  • Data quality + lineage - ensuring the quality of data is governance and documented in accordance with Group-wide standards.
  • Machine Learning, stats, modelling etc - knowledge of the practical application of these techniques is required.
Quantitative Researchers develop and test highly automated quantitative trading strategies using sophisticated quantitative/statistical techniques for strategies ranging from Equity/Non-Equity Statistical Arbitrage, Systematic Fundamental Equity L/S, Systematic CTA/Managed Futures and Fundamental FICC.


  • Assist in developing core algorithms and models leading directly to trading decisions
  • Work closely with traders to interpret valuations and develop next generation models and analytics
  • Evaluate financial data vendors; evaluate and work with new data sources and analytics packages in developing investment strategies
  • Provide high level technical and investment analytics support to trading desks
  • Support research and statistical analyses about securities and commodities
  • Work closely with other researchers to develop and continuously improve upon mathematical models, and help translate algorithms into code


  • Bachelor’s degree, or equivalent experience, preferably in Statistics, Computer Science, Mathematics, IEOR, Finance, Accounting, Economics, or a related field
  • Demonstrated ability to complete high-level, investment-related research
  • Prior experience in a quantitative role within a trading environment or experience in a position applying advanced quantitative techniques to solving highly complex data intensive problems
  • Strong analytical skills; experience working with and analyzing large datasets
  • Strong mathematical and statistical modeling skills (i.e. time-series and cross-sectional skills) preferred Proficiency in coding, with experience using statistical packages (e.g. R, Matlab)
  • Exposure to scripting (e.g. Python, Perl); C/C++ a plus but not required
  • Demonstrated interest in or knowledge of investments, derivatives, asset pricing, empirical anomalies, macroeconomic analysis and market micro-structure
  • Prior experience with equities, convertible arbitrage, fixed income and/or commodities
  • Understanding of the modeling of risk and dynamics of linear and non-linear financial products
  • Strong understanding of international accounting rules and familiarity with global market structure
  • Familiarity with portfolio construction analytics and some exposure to quantitative portfolio management