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Data Science Consulting Services

SoftTeco’s data science services are aimed at transforming your data into a valuable business asset. We help you identify inefficiencies, optimize inner processes, and devise long-term strategies to grow your business.

18

years on the IT market

500

employees

450

successful projects

75

client locations

SoftTeco’s data science services

Data science consulting

Our data science strategy consulting helps business owners define the most suitable data science roadmap. We enable you to uncover patterns in your data, build predictive capabilities, and generate actionable insights to facilitate strategic planning. To achieve this, our experts:

  • Analyze your business goals, market needs, and data
  • Analyze diverse and complex datasets
  • Recommend an optimal technology stack and tools
  • Design and validate data science use cases

Data engineering consulting

Data engineering specialists provide expert guidance on building, managing, and optimizing data pipelines and infrastructure. This helps businesses turn raw information into meaningful insights for data-driven decision-making. We advise on how to:

  • Generate raw information from various sources
  • Choose a solution for data storage and management
  • Integrate data from various sources into a central storage system
  • Conduct data cleansing, validation, normalization, and aggregation

Data science solution delivery

We support the end-to-end delivery of data science solutions, from early validation to production deployment. Our developers help turn ML models into reliable, scalable systems that operate seamlessly in real-world environments. As part of this service, SoftTeco helps to:

  • Develop and validate MVPs or PoCs for data science use cases
  • Build, train, and fine-tune custom ML models
  • Integrate ML solutions into existing systems and workflows
  • Deploy, monitor, and maintain ML models in production

Data science solution modernization

If you already have a data science system and need to optimize it to meet evolving business needs, rely on SoftTeco. We analyze your current solution, identify pain points, and design the most appropriate roadmap for its modernization. Our team of experts are ready to:

  • Add new features
  • Integrate new systems, such as ERP, analytics tools
  • Design and implement new ML models
  • Review and optimize the existing architecture

Data science solution support

Once your system is deployed, we offer post-launch support and maintenance services. It includes performance monitoring, data management support, fine-tuning of ML models, debugging, and further solution improvements. Our experts help you:

  • Quickly identify and resolve issues and bugs
  • Monitor, fine-tune, and improve the ML model and data
  • Maintain stable solution infrastructure
  • Provide detailed documentation and training

DataOps services

Establish a transparent, effective data flow across your organization with our DataOps services. Using advanced analytics, automation, CI/CD, and monitoring, our engineers help you streamline data pipeline, improve the accuracy of insights, and share data efficiently across departments. We advise on how to:

  • Monitor and optimize data pipelines
  • Automate data flow
  • Update data pipelines
  • Implement version control for data and models

Supplementary services SoftTeco offers

01

Machine learning development

SoftTeco’s engineers design, build, and optimize machine learning solutions across the full lifecycle, from data preparation and model training to integration. Our ML services cover a range of use cases, including predictive analytics, computer vision solutions, and AI agents development.

02

Business intelligence implementation

To centralize your information and ensure it is available in suitable formats, we offer scalable BI system implementation. Our BI developers and data analysts configure and customize BI solutions to meet your needs and integrate with all needed data sources, enabling you to quickly extract insights from data.

03

Big data management

SoftTeco helps businesses manage diverse and massive data as effectively as possible, collecting it from different sources. As part of this service, our data engineers can recommend the most suitable storage solutions, big data processing and management tools according to your needs and requirements.

04

Data storage configuration

We develop various types of data storage for specific purposes, can optimize it or help you transfer data to an existing one. Based on your needs, our engineers build and set up data storage infrastructure, such as data warehouses, data lakes, lakehouses, operational data stores, and data marts.

05

Data analytics and reporting

SoftTeco helps you turn raw data into structured insights for measurable business operations tracking. To achieve this, our experts design analytics models, define KPIs, and set up automated reporting so you receive accurate, consistent information on a regular basis.

06

Data visualization

We create custom dashboards and reports as well as implement full-scale data visualization solutions. Our service helps companies make data easily accessible and understandable for all stakeholders and, as a result, facilitate the decision-making process.

Turn your data into powerful insights and predictions with SoftTeco

Data science applications across industries

Healthcare

Healthcare providers can improve patient outcomes, hospital workflows, and employees productivity through such data science solutions as:

  • Patient monitoring
  • Medical imaging
  • Drug discovery
  • Disease prediction and diagnostics
Data Science Consulting
Data Science Consulting

Banking & fintech

Banks and financial institutions can speed up and improve financial operations, decision-making, and customer experience through: 

  • Assessing financial risks
  • Managing investment portfolios
  • Fraud detection and prevention
  • Calculating customer lifetime value 
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Manufacturing

Manufacturing organizations can move from reactive to predictive maintenance, improve inventory management, and increase overall efficiency through:

  • Quality control
  • Supply chain optimization
  • Financial losses prediction
  • Schedule preventative maintenance
Data Science Consulting
Data Science Consulting

Retail

Retail firms can optimize their processes, maximize sales, and customer satisfaction by leveraging such data science systems as:

  • Demand forecasting
  • Inventory optimization
  • Customer segmentation
  • Personalized product recommendations
Data Science Consulting
Data Science Consulting

Automotive

Automotive companies can improve their automobile production, improve vehicle performance, quality and driving experience through:

  • Vehicle dynamics and safety
  • Tire pressure monitoring
  • Fuel consumption analysis
  • Engine performance monitoring
Data Science Consulting
Data Science Consulting

Transportation & logistics

Logistics companies can optimize delivery routes, accurately forecast the supply and demand cycles, and reduce fuel and operational costs through:

  • Route optimization
  • Tracking shipments
  • Gathering data about traffic trends
  • Collecting data about previous journeys
Data Science Consulting
Data Science Consulting

Agriculture

Agriculture companies can optimize resource use, improve crop yields, and minimize weather-related risks through:

  • Soil health assessment
  • Pest and disease detection
  • Yield prediction and optimization
  • Weather prediction and management
Data Science Consulting
Data Science Consulting

Telecom

Telecom organizations can improve the quality of network, price strategies, effectively equipment failures, and deliver personalized offerings through:

  • Price optimization
  • Identifying usage patterns
  • Network optimization
  • Determining fraud and equipment failures
Data Science Consulting
Data Science Consulting

Oil & gas

Oil and gas companies leverage data science to improve the processes and decisions related to oil and natural gas exploration, production, and refinement through:

  • Identifying ideal drilling sites
  • Asset performance optimization
  • Equipment maintenance prediction
  • Prediction of ideal drilling pressures and angles
Data Science Consulting
Data Science Consulting

Hospitality & tourism

Data science solutions can help hotels optimize revenue, enhance guest experience, predict trends, and remain competitive through:

  • Marketing efforts enhancement
  • Occupancy optimization
  • Customer churn analysis
  • Personalized guest experiences
Data Science Consulting
Data Science Consulting

Media & entertainment

Media and entertainment companies can optimize content creation, enhance consumer engagement, and advance marketing activities through:

  • Content personalization
  • Customer insights analysis
  • Predictive analytics for audience engagement
  • Content distribution optimization on social media
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Data Science Consulting
Data Science Consulting

Our data science expertise

Our data science consulting firm uses a variety of methods and technologies to design and implement advanced data science solutions.

Agentic AI

SoftTeco leverages agentic AI to build systems that independently analyze data, make decisions, and take actions in real-time. By applying this expertise, we help companies across industries adopt it to operate more efficiently, reduce manual work, and improve decision accuracy.

Business impact:

  • Reduced costs through automated processes and minimized manual intervention
  • Accelerated business processes via reduced decision-making time
  • Improved customer experience with fast and accurate responses
  • Sales and marketing automation through optimized consumer touchpoints

Statistical programming

Our data science specialists leverage programming languages such as R, Python, SAS, and Julia, statistical methods, regression analysis, and predictive modeling. They use diverse statistical computing tools and methods to extract insights from data, design robust experiments, and build predictive models.

Business impact:

  • Streamlined data analysis process without significant manual handling
  • Better decision-making through rigorous statistical analysis
  • Accurate results by using validated statistical methods
  • Improved forecasting accuracy with predictive modeling

Predictive analytics

We use regression, ML-based predictive techniques, and predictive analytics tools to help businesses make accurate predictions based on current and historical data. Our data scientists can forecast upcoming events, market trends, and strengthen risk management capabilities.

Business impact:

  • Better sales and marketing efforts through informed predictions
  • Stronger business strategy by anticipating future trends
  • Risk reduction due to its early identification and prevention
  • Competitive advantage by addressing opportunities and challenges proactively

Machine Learning

Our development teams build and deploy ML models with supervised learning for customer segmentation, risk modeling, natural language processing (NLP), and computer vision. They apply unsupervised ML to adapt ML models to domain-specific tasks.

Business impact:

  • Automated and optimized repetitive tasks and business workflows
  • Improved operational efficiency through data-driven insights
  • Future trends forecasting based on historical data and current variables
  • Risk mitigation through data analysis and potential threats identification

Neural networks

We utilize modern neural architectures to solve complex problems in computer vision, natural language processing, and data modeling. With expertise in deep learning, SoftTeco develops scalable AI systems for real-world apps that go beyond the capabilities of traditional algorithms or human analysis.

Business impact:

  • Improved cybersecurity through anomaly detection and attack pattern prediction
  • High accuracy by detecting complex patterns beyond human analysts
  • Early diagnosis and outcome prediction with superior accuracy
  • Enhanced fraud detection through deep pattern recognition

Why choose SoftTeco as your data engineering company?

18+ years in software development, data science, and business intelligence
ISO 27001 and ISO 9001 certified for information security and service quality
300+ developers, ML engineers, data scientists, and business analysts
Recognized by Clutch as one of the top custom software development
Project delivery on-time and within budget

Our data science projects

ML-powered recommendation engine 

SoftTeco created a subscription-based platform that offers royalty-free music, sound effects, and stock footage. We incorporated an ML-powered recommendation system that analyzes user profiles, detects behavioral patterns, and predicts content relevance. Our ML engineers implemented a semi-automated marketing mix modeling solution. It enables companies to make data-driven decisions on content suggestions and allocate marketing budgets more effectively.

SoftTeco built a mobile application for real-time heart monitoring. A key part of the solution was the machine learning model and algorithm that our engineers created to process ultrasound images. The app uses TensorFlow for deep learning-based image analysis, including image segmentation and feature extraction. ML models detect heart structures and calculate critical parameters to enable faster, more accurate heart decisions.

SoftTeco developed an ML-powered application to track and monitor bees. Our team was responsible for defining the product’s architecture, performing data mining, data processing, and training neural networks. We integrated computer vision to accurately count the number of bees in the hive. Our BI developers designed clear charts and graphs to help users track the dynamics of the hive’s growth and make informed decisions to maintain healthy bees.

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Business benefits of data science implementation

Improved operational efficiency

Data science enables businesses to gather and analyse large volumes of data. By doing so, companies can identify inefficiencies, optimize operations, and improve overall productivity.

Better decision-making

By using data science, organizations can identify trends, detect patterns, and predict future outcomes. Companies that use analytics are 5 times more likely to make faster decisions with quantifiable evidence.

Improved user experience

Data science enables a much deeper analysis of customer data and helps businesses reshape their marketing strategy. 36% of businesses use real-time analytics to improve customer engagement and reduce churn.

New revenue streams

Data can provide valuable insights into customer behavior, quality of goods and services, and employee efficiency. By analysing this data and acting on insights, companies can identify new revenue streams and growth opportunities.

Calculate the cost of your team

The calculator will help you estimate the total cost of the team needed to build your data science solution based on the number of specialists, their rates, and timeline.

FAQ

How much does a data science solution cost?

The cost of implementing a data science solution can range from $5,000–$20,000 for small businesses, $10,000–$100,000 for medium businesses, and $20,000–$300,000+ for large ones. The cost of such a system can vary significantly and depends on project scope, tech expertise, tools and technologies used, and industry-specific requirements.

How long does it take to implement a data science solution?

To implement a data science solution (proof-of-concept model) requires 3–8 weeks, a production ML pipeline for a single application 8–20 weeks, and a large AI/ML product 4–12+ months. The duration of a project can vary and depends on data quality, project scope, team composition, tooling, and infrastructure maturity, as well as regulatory, security, and integration complexity.

What does a data science consultant do?

Data science specialists help businesses to prepare, analyse, and model datasets to design custom-fit, advanced analytical and AI solutions. They are proficient in statistics, data mining and analysis, machine learning, visualization, and specialized programming languages, such as Python, and R.

What is the difference between data science and traditional analytics?

Traditional data analytics primarily works with past and present data to understand what happened and what is happening now. Data science also uses historical and current data, along with machine learning and advanced algorithms, to build predictive models and forecast future outcomes.

Who is included on a data science team at your company?

At SoftTeco, we formed a dedicated data science and machine learning department that consists of experts with deep expertise.

Data scientists find and interpret rich data sources, combine them, and use ML to build models that help extract insights from complex data.
Data analysts collect, clean, analyze, and prepare data to present insights in a сlear and understandable format.
Data architects design, create, manage, and optimize an organization’s data architecture, set policies for data storage, accuracy, and accessibility, and integrate new data technologies into existing IT infrastructures.
Machine learning engineers design, build, and deploy ML models into production systems, maintain and improve existing systems.
Data engineers develop, test, and maintain data pipelines and solution architectures.
Data science architects design and maintain the architecture of data science applications.
Data annotators train ML models to generate accurate results automatically.

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