Data Science Consulting Services

Data science and machine learning consulting - ScienceSoft

Data science services include data science consulting, development and support to enable companies to run experiments on their data in search of business insights.

Since 1989, ScienceSoft has been applying data science in its different forms ranging from statistics to machine learning (including its most recent technique – deep learning) to meet the most deliberate analytics needs of our clients.

Your Analytics neither Reveals True Reasons behind Low Performance, nor Enables Accurate Predictions?
We can share and implement data science best practices to drive your decision-making with careful forecasting and effective root-cause analysis.

Benefits that Data Science Brings

We, at ScienceSoft, are devoted to data science services as we see many improvements that it can bring to businesses, regardless of the industry they represent.

Optimized supply chain management

Our data scientists can apply an ARIMA model or a deep neural network to generate reliable demand predictions. We can build neural networks or apply ML algorithms, such as hierarchical clustering and multi-class support vector machines, to evaluate your suppliers and assess the risks associated with each of them.

Improved production efficiency

We can help you fight low overall equipment effectiveness (OEE) by identifying the root causes for availability, performance and quality losses. We apply machine learning techniques to achieve predictive maintenance, undisrupted functioning, and enhanced product quality.

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  • Predictive maintenance

    Our data scientists can analyze the data from sensors installed at monitored machinery parts to understand the patterns in machinery functioning so that you could plan its maintenance more efficiently. One of the ways to solve this task is to apply Naïve Bayes algorithm to classify normal and pre-failure events. To get more insights, we can further classify the cases based on the time left until a breakdown. For instance, a failure that can happen within 24 hours gets a red color, a failure within 24h – 72h – yellow, a failure in more than 72h – green color.

  • Operational intelligence

    Even if the monitored parameters seem to be fine when considered individually, their particular combination can still witness an upcoming breakdown. With the help of data science, we can identify such hidden interdependencies and their potential consequences. As a result, operators can receive real-time alerts and solve issues themselves or escalate them to the attention of the maintenance team.

  • Enhanced product quality

    Machine learning techniques are helpful when you need to identify process disruptions at each production stage. We compare the actual and expected duration of each operation, as well as check temperature, vibration and other parameters. All this, to move beyond simple thresholds to really complex dependencies and identify the deviations that may affect product quality as early as possible. Having learned at some early stages that raw materials or parts are defective, you won’t waste your time and resources on continuing with them at all the remaining production stages. This can also save the entire manufacturing process from being affected by a defective part or component.

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Personalized customer experience

Applying machine learning techniques, such as collaborative or content-based filtering (or both of them combined), we can design a recommendation engine to boost the sales of your ecommerce store. Such an engine can help you make your customers happier with relevant product offers. A webpage showing personalized content, a mobile app with promo offers that spark customers’ interest, as well as relevant email campaigns are also among the gains that you can get with data science.

Sales effectiveness

We can implement machine learning-based lead and opportunity scoring so that you’re sure that your sales team adheres to the chosen business strategy, as well as wisely prioritizes their efforts.

Besides, we can create a machine learning model to make your communication with customers stellar. Trained to detect attitude markers and recognize your customers’ mood, the model will signal your sales team if a particular customer experiences negative emotions.

We can provide you with a machine learning model to help you streamline the sales process by providing your sales team with clever next-step recommendations.

Customer behavior prediction

We’ll apply machine learning algorithms to provide you with accurate predictions of your customers’ behavior. For example, you’ll be able to assess whether it’s likely that your customer is a late payer, how they will react to price changes or to promotions. We can also help you identify potential churners so that you can design the strategies to prevent their loss.

Image analysis

Using machine-learning-based analysis, our data scientists can turn images or videos into meaningful info. You can use these insights to solve various business tasks, such as automated visual inspection, facial or emotion recognition, grading, and counting.

Select your Data Science Consulting model

Data Science Solution Implementation

Do you consider building a data science solution in your company, but lack needed experience and resources? ScienceSoft is ready to implement its best practices to ensure a smoothly functioning data science solution that suits your business needs.

Data Science Improvement Consulting

If you’ve encountered a problem (noisy or dirty data, inaccurate predictions, etc.) in your data science project, we can serve as your think tank to help you figure out how to adjust your data science solution to be make your project pay dividends.

Data Science Ongoing Consulting and Support

If you seek continuous support and evolution of your data science initiative, our team will closely cooperate with your subject matter experts and implementation team to provide ongoing recommendations and ensure the models’ continuous improvement. This will increase the quality of insights and help adjust the models to the changing environment.

Methods and Technologies we use

To get to the valuable insights that your data hides, we apply both proven statistical methods and elaborate machine learning algorithms, including such intricate techniques as deep neural networks with 10+ hidden layers.

Methods

Statistics methods
  • Descriptive statistics
  • ARMA
  • ARIMA
  • Bayesian inference, etc.
Non-NN machine learning methods
  • Supervised learning algorithms, such as decision trees, linear regression, logistic regression, 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.
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

Technologies

Programming languages

Python
R
Java
Scala

Frameworks

Apache Mahout
Caffe
Apache MXNet
TensorFlow
Torch

Libraries

Spark's Machine Learning Library (MLlib)
Amazon Machine Learning
Azure ML Studio
Theano
Keras
Scikit-learn
Gensim
SpaCy
OUR DATA SCIENCE PORTFOLIO
Stop Missing Out on Data Science Benefits!
If you are ready to employ elaborate analytical technologies such as machine learning and deep neural networks to improve performance and find new business opportunities, ScienceSoft can back up your project with data science best practices.