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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 has been providing companies with data science services to enable them to exploit growth and process improvement opportunities.
What Makes ScienceSoft a Reliable DSaaS Vendor
- 35 years in data science and data analytics.
- 11 years in big data.
- 19 years of experience in rendering data warehouse services.
- Hands-on experience with all major languages, libraries and cloud services for data science.
- ISO 9001 and ISO 27001 certified to assure the quality of the data science services and the security of client data.
- Domain experience in 30 industries, including healthcare, banking, lending, investment, insurance, retail, ecommerce, professional services, manufacturing, transportation and logistics, energy, telecommunications, and more.
Analytics Domains We Cover with DSaaS and Value You Get
Risk management
Quality management
Our Featured Data Science Projects
22 results for:
Portfolio Management and Trading Automation Software Powered by Data Science
ScienceSoft developed a fully featured algorithmic trading solution with custom predictive and prescriptive analytics models at its core. The software provides data-driven guidance on security investments for NASDAQ and AMEX traders and automates trading execution.
Case Study
Complex Semantic Search Engine to Drive High R&D ROI
An innovative semantic analysis software to streamline research and development for large enterprises. The software enables intuitive search and navigation across 15 million patents, 3,000 scientific websites, and 8,000 scientific effect studies.
LLM-Supported Smart Search for Mobile Banking App Users
In just 4 weeks, ScienceSoft provided a top high-tech bank with a functional concept, a technical design, and an implementation plan for an LLM-powered smart search solution. Our advice on the cost-effective tech stack and hardware ensured optimized project investments.
Real-Time LED Display Monitoring Software for the World’s LED Industry Leader
ScienceSoft developed a cross-platform application for Linux and Windows for real-time video monitoring, error detection and notification. With the app, the Client can instantly identify problems with showing advertisements on its LED displays.
Case Study
Lung Cancer Detection Application for bioAffinity Technologies
In 2 months, ScienceSoft provided a US-based biotechnology company with a desktop app for lung cancer detection. The app ensures 100% stable generation of comprehensive diagnostic reports based on analysis of flow cytometry data.
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
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.
Choose Your Service Option
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:
Support Decision-Making with Advanced Analytics
