Data Science Services Company

Take advantage of a powerful mixture of machine learning, data analysis, business intelligence, and other related methods to transform raw information into valuable insights and help any business prosper.

Emerline teams select the right data science approaches and technologies to turn your data into sound business solutions.

Data science technologies

Here are the technologies, tools, and databases our teams use for the successful data science project implementation:

Technologies and Languages

Python
R programming
Matlab
Swift

Databases and Frameworks

MySQL
MongoDB
Scikit-learn
Pandas
Statsmodels
Prophet
Tensorflow
Keras
NumPy
SciPy
XgBoost
LightGbm
NLTK
Skype chatbot framework
OpenCV
BigARTM
Core ML
Apple Accelerate framework

Neural networks

CNN (YOLO, SSD, ResNet)
RNN

Data science methods

With respect to your business requirements and objectives, we will assist you with your data science project, taking advantage of the following methods:

Statistics methods

  • Descriptive statistics
  • ARMA
  • ARIMA
  • Bayesian inference, etc.

Non-neural-network machine learning methods

  • Supervised learning algorithms, such as decision trees, linear regression, logistic regression, and support vector machines
  • Unsupervised learning algorithms, for example, K-means clustering and hierarchical clustering
  • Reinforcement learning methods, such as Q-learning, SARSA, temporal differences method, etc.

Neural networks, including deep learning

  • Convolutional and recurrent neural networks (including LSTM and GRU)
  • Autoencoders
  • Generative adversarial networks (GANs)
  • Deep Q-network (DQN)
  • Bayesian deep learning

Statistics methods

  • Descriptive statistics
  • ARMA
  • ARIMA
  • Bayesian inference, etc.

Non-neural-network machine learning methods

  • Supervised learning algorithms, such as decision trees, linear regression, logistic regression, and support vector machines
  • Unsupervised learning algorithms, for example, K-means clustering and hierarchical clustering
  • Reinforcement learning methods, such as Q-learning, SARSA, temporal differences method, etc.

Neural networks, including deep learning

  • Convolutional and recurrent neural networks (including LSTM and GRU)
  • Autoencoders
  • Generative adversarial networks (GANs)
  • Deep Q-network (DQN)
  • Bayesian deep learning

Why choose us?

What makes Emerline stand out from other companies that offer data science services? Here are some of our strengths:

Solid expertise in the sector

The quality of our data science professional services is proven by numerous successful projects, delivered to both startups and enterprises.

Focus on business demands

Our data science services are geared towards finding and suggesting proper software or service that contributes to the customer’s revenue growth and improves the efficiency of operations.

Custom-made development

Custom-made development makes each solution capable of being integrated with your existing internal systems. Our experts will also assist with deployment and maintenance.

Top-notch software services with no strings attached

No need for you to worry about potential project risks or issues — we'll meet the challenges. You simply enjoy first-class services within a predicted scope, timeframe, and budget.

We deliver fast and on budget

We understand your vital need to be faster in order to outperform the competitors in your niche, so we deliver in no time and meet your requirements within a predefined budget.

Own R&D department

We continuously accumulate our expertise and invest in researching and testing the latest technologies before recommending them to our customers.

Just give us the idea, and we'll do the rest

It doesn't matter for us whether you have only a vague concept or a detailed specification — our team will put your business expectations into a reality.

There are no restrictions on the project size

We are flexible in terms of the project size and ready to consider any budget, timelines, or scope.

High level of engagement and support

No question will remain unanswered — we accompany our clients along the way to a complete functioning solution.

Solid expertise in the sector

The quality of our data science professional services is proven by numerous successful projects, delivered to both startups and enterprises.

Focus on business demands

Our data science services are geared towards finding and suggesting proper software or service that contributes to the customer’s revenue growth and improves the efficiency of operations.

Custom-made development

Custom-made development makes each solution capable of being integrated with your existing internal systems. Our experts will also assist with deployment and maintenance.

Top-notch software services with no strings attached

No need for you to worry about potential project risks or issues — we'll meet the challenges. You simply enjoy first-class services within a predicted scope, timeframe, and budget.

We deliver fast and on budget

We understand your vital need to be faster in order to outperform the competitors in your niche, so we deliver in no time and meet your requirements within a predefined budget.

Own R&D department

We continuously accumulate our expertise and invest in researching and testing the latest technologies before recommending them to our customers.

Just give us the idea, and we'll do the rest

It doesn't matter for us whether you have only a vague concept or a detailed specification — our team will put your business expectations into a reality.

There are no restrictions on the project size

We are flexible in terms of the project size and ready to consider any budget, timelines, or scope.

Business benefits of data science services

If you wonder how data science solutions can help you in reaching new heights, here are some of the ways you can benefit from them:

Sales and Marketing

Retail and Telecom

Medicine and Healthcare

Banking and Finance

Media and Entertainment

The beneficial use of data in Sales and Marketing covers detecting and preventing insurance fraud or defining product needs and target prices for specific customers.

Here, data serves as a path to revenue, so lifetime value (LTV) calculation is the essential metrics to measure net income referring to the relationship with a customer. Another aspect is to manipulate data for customer churn prediction and audience segmentation.

The value of data shouldn’t be underestimated in this domain as well. Anomaly detection in the scans will be more accurate. Data science approaches contribute to better processing of life cycle time series.

In fintech, data science opens up space for a better understanding of customer’s banking habits through analytics, as well as helps specialists suggest relevant financial advice at appropriate times.

Allowing to define and understand real-time, media content usage patterns, data science in media and entertainment helps industry players create targeted content for different audiences, effectively measure its performance, and create useful recommendations.