Data Science as a Service
Data science as a service allows companies to get business insights leveraging advanced analytics technologies, including deep learning, without investing in in-house data science competencies.
Since 1989, ScienceSoft provides companies with data science services to enable them to exploit growth and process improvement opportunities.
- 33 years in data science and data analytics.
- 9 years in big data.
- 17 years of experience in rendering data warehouse services.
- Hands-on experience with all major languages, libraries and cloud services for data science.
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ScienceSoft USA Corporation is listed among The Americas’ Fastest-Growing Companies 2022 by Financial Times.
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ISO 9001 and ISO 27001-certified to assure the quality of the data science services and the security of the customers' data.
- Domain experience in 30 industries, including manufacturing, energy, retail and wholesale, professional services, healthcare, financial services, transportation and logistics, telecommunications.
Operational intelligence
Supply chain management
Production management
Predictive maintenance
Risk management
Customer analytics
Quality management
Frequently Asked Questions
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What value do we get when choosing data science as a service?
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How can we be sure of the quality and speed of analytics insights?DSaaS delivery is based on the agreed service quality KPIs, which may include:
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Will our data be secure?Data safety is ensured through:
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Data Science Technologies and Methods We Use
Programming languages
Machine learning frameworks and libraries
Frameworks
Libraries
Data science cloud services
Big data
Data visualization
Statistics methods
Descriptive statistics
ARMA
ARIMA
Bayesian inference
Machine learning algorithms
Supervised learning
Unsupervised learning
Reinforcement learning
Neural networks, including deep learning
Neural networks
Convolutional and recurrent neural networks (LSTM, GRU, etc.)
Autoencoders (VAE, DAE, SAE, etc.)
Generative adversarial networks (GANs)
Deep Q-Network (DQN)
Bayesian deep learning
Data Science Consulting for Electric Energy Consumption Analysis and Forecasting
ScienceSoft suggested high-level software architecture and provided detailed recommendations on creating machine learning models for electric energy consumption analysis and forecasting software, which would allow electric power companies to optimize their load management and price determination procedures.
Data Science Implementation for Sales Analysis and Forecasting
ScienceSoft supported a leading FMCG manufacturer by delivering science-based sales forecasting and attainable sales targets.
Big Data Implementation for Advertising Channel Analysis in 10+ Countries
ScienceSoft implemented a big data analytics system, which allowed one of the top market research companies to carry out comprehensive advertising channel analysis for different markets.
Development of a Big Data Solution for IoT Pet Trackers
To support a long-term customer in a new service launch, ScienceSoft delivered a scalable IoT data management solution that allowed processing 30,000+ events per second from 1 million devices.
Pricing Models for Data Science as a Service
Monthly subscription fee
Recommended when the engagement scope is clear, for outsourcing a particular number of data science talents to perform the required activities.
Time and Material
Recommended when the engagement scope is unclear.
For companies with no data science capabilities
We offer:
- Analysis of business needs driving the company to apply data science.
- Source data preparation and cleansing.
- Development, training, testing and deployment of machine learning models.
- ML model tuning.
- Delivering data science output in an agreed format.
- Integrating ML models into an application for users’ self-service, if required.
For companies that need to enhance their data science insights/initiatives
We offer:
- Analyzing your business needs and the existing data science environment.
- Evaluating the existing ML models, ML debugging and error analysis.
- Data cleansing.
- Continuous tuning and training of ML models for increased ML model accuracy.
- Adding new data to the ML models for deeper insight.
- Building new ML models to address new business and data analytics questions.
Why Turn to DSaaS Right Now
An expert data science team can help you quickly embrace data science for meeting particular advanced analytics objectives and achieving the following benefits:
