Data ScienceBack Expertise
Enter the age of data. We empower our clients with valuable insights by offering design and implementation of predictive analytics algorithms and build platforms that deliver recommendation engines, fraud detection, BI tools and other data-driven insights.
Types of projects
- Image processing and pattern recognition
It’s never been easier to produce images and to communicate with them than today - everybody has a camera or a drone, and we are surrounded by emojis, memes or selfies. Although they are informative to humans, machines see them as lots of unstructured data which makes them difficult to classify or extract meaningful information from. That is to say, difficult without some help from data science.
If properly processed, normalized and fed to carefully designed machine learning models, images and videos (which are treated as sequences of images) could be used to prevent crime in crowd analysis products, to detect patterns and automate tasks (license plates reading, OCR) or to augment working environment for humans.
- Natural language processing
If data is the new king, then context is the queen, and this is nowhere more clear than in the application of natural language processing. Human-to-human communication is very context-dependent so every machine algorithm that is to serve as an intelligent agent, whether a chatbot, sentiment analysis or a smart fridge, should learn about (or be thought of) different contexts of the words, phrases and sentences that humans use in communication. The similarity between natural language constructs inside a specific context is the end-goal of many clever machine learning algorithms. We employ word embedding techniques to either produce latent topics over a collection of documents, also known as topic modeling or to identify the semantic similarity between individual terms, for example, with word2vec embedding, over a textual corpus.
- Behavior analytics and Personalization
Product or service personalization is one of the first added values you can deliver when turning to a data-driven approach. By collecting data about users’ behavior like transactions made or products engaged, and without compromising privacy, businesses powered by data science algorithms are able to recommend similar products to users or deliver in-time solutions. As users, we all have our own relationships with recommendation engines or personalized ads, but their effectiveness could be easily noticeable.
Additionally, the same data companies possess drive algorithms that could help them optimize cross-selling, storage or product placement through market basket analysis, govern digital marketing campaigns or save valuable customers with churn analysis.
- Anomaly Detection
Not every outlier is an anomaly but outliers are the most common and usual suspects. However, anomaly detection is far more complex than simple outlier detection and in essence a hard problem to solve. Anomalous behavior of systems or malicious tendencies of people, ie. fraud detection, could be hard to spot and even harder to predict from streaming time series data. When looking at hundreds of infrastructural metrics and logs, interesting anomalies are usually not in each individual spike but hidden as contextual anomalies threatening to endanger the system. We throw everything we’ve got at these problems, from data engineering expertise and classical forecasting techniques applied to individual metrics to multivariate analyses with deep learning sequence prediction and pattern recognition of overall system behavior.
- Insights Report
Our team of Data Scientists and Analysts can help you understand the value of business data you already have or plan to collect. From our experience, there are 2 types of data-aware organizations: those that are new to data-driven approach and those that have been leveraging data but want to shift toward more advanced analytics and their application.
We like to take a phased approach where real value and actionable items delivered to client from each phase allow for better progress tracking, more maneuverability during project execution and, most importantly, the feedback loop that ensures the final product is a perfect match for specific business needs.