Data Science Services
Decipher your data. Make better decisions.
Gather business insights and stay competitive with our data science services. Work with the top 1% of tech talent, onboarded within 2-3 weeks.
30+ companies rely on our top 1% tech talent.
Data Science Services We Provide
1. Predictive Analytics
Analyze historical data to forecast future outcomes and trends. Predictive analytics help stakeholders make informed business decisions and develop proactive strategies. Real-life applications include anything from credit scoring to forecasting disease outbreaks.
We utilize tools and frameworks such as Python’s Scikit-learn, R, and TensorFlow to craft and refine predictive models.
2. Machine Learning
What do self-driving cars, Alexa, and Netflix’s recommendation engine have in common? They all rely on machine learning.
Machine learning is a key component of data science. It allows computers to learn from data and make smart decisions. This technology can handle routine tasks, predict trends, and offer intelligent insights. Our engineers use the latest tools and frameworks like TensorFlow, Keras, and PyTorch to implement ML solutions.
3. Natural Language Processing
Natural Language Processing (NLP) enables machines to understand, interpret, and generate human language. For example, it’s often used in chatbots and virtual assistants. Businesses also leverage NLP to build applications like GPT-4 or text-to-speech software.
We use libraries such as NLTK, SpaCy, and the Transformers library from Hugging Face for our NLP tasks
4. Data Visualization
Transform complex data into intuitive, interactive visuals. Glean insights, identify trends, and make better data-driven decisions. Social media analytics tools like Hootsuite or charting platforms like TradingView are great examples of data visualization at work.
We create compelling visuals, dashboards, and reports using tools and frameworks like Matplotlib, Seaborn, and Google Visualization API.
5. Data Pipelines
Data pipelines streamline the process of collecting, transforming, and storing data for analysis or further processing. For example, a retail chain might use data pipelines to analyze customer behavior and purchase history and optimize inventory management.
To design and manage these pipelines, we employ tools and frameworks such as Apache Kafka, Apache NiFi, and Apache Airflow.
6. Business Intelligence (BI)
Harness your data and get actionable, real-time insights. Make more informed business decisions about your staff, customers, finances, and more. BI is used for anything from risk management to quality control.
We use BI platforms and tools like Power BI, Tableau, and QlikView to analyze, visualize, and uncover useful insights.
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Data Science Services We Provide
Key Facts about Data Science Services
Best Practices for Data Science
Why Choose Voltera for Data Science Services
Our process. Simple, seamless, streamlined.
Frequently Asked Questions (FAQ)
Key Facts about Data Science Services
1. Access Niche Specialists
Outsourcing provides access to skilled data scientists and tech talent from all over the world. It makes it easier to hire specialists with industry experience and niche expertise.
2. Cost-Effective Scaling
Want less overhead and admin work? When you rely on a third party, you won’t need to worry about costs such as health insurance, bonuses, software licenses, hardware, and more.
3. Focus on Core Business
Companies can concentrate on core activities while external experts handle the data and analytics strategy. No more recruitment hassles or overburdening your in-house team.
4. Rapid Implementation and Scalability
External teams have established processes in place. Reliable partners can implement your desired solutions faster and help you scale.
5. Tap into the Latest Technologies
Outsourced professionals are up-to-date on the latest data science technologies and best practices. They can share relevant insights and competitive strategies with your in-house team.
6. Diverse Perspectives
Outsourced experts come from a variety of different backgrounds and cultures. This could improve teamwork, problem-solving and drive innovation.
Data science is crucial for businesses because it turns raw data into meaningful insights. By analyzing data, companies can better understand customer behavior, predict trends, and enhance decision-making.
Best Practices for Data Science
Ensure all data used is valid, accurate, and consistent. Incorporate continuous data validation techniques during deployment to account for changes over time.
Implement strategies like imputation or deletion to manage missing data efficiently.
Leverage cloud platforms for scalable and flexible data storage and processing.
Ensure efficient data flow from ingestion to processing and visualization.
Choose algorithms suited to the problem type and data characteristics. Also, consider computational complexity and algorithm interpretability during the selection process.
Leverage standalone metrics and visual evaluation methods to assess model performance.
Monitor the model performance. Focus on the inputs and outputs, ensuring no significant deviation that might indicate issues with data quality or model drift.
Implement systems to automatically retrain models with fresh data. Monitor and validate the model post-retraining in case the new data has degraded performance.
Employ version control systems to manage code and model versions efficiently.
Leverage platforms that enhance collaboration among team members.
Use workflow management tools to automate and streamline data science processes.
Maintain thorough and clear documentation for models, codes, and experiments to ensure reproducibility and knowledge sharing.
Implement techniques such as nullification, equalization, and reweighing to identify and minimize biases in data and models. Bias detection tools like IBM’s AI Fairness 360 can also help.
Ensure that model decisions can be explained to and understood by stakeholders.
Make sure your data storage, transfer, and access management comply with local and international data protection regulations.
Maintain transparent and auditable processes to comply with regulatory and organizational standards.
100s of companies worldwide trust us for their Data Science services.
Why Choose Voltera for Data Science Services
Tailored Solutions
We build custom business intelligence solutions to give you a competitive edge. A personalized, data-driven approach helps you uncover hidden opportunities, streamline operations, and make more informed business decisions.
Top 1% of QA Talent
Starting with your business goals, we create a comprehensive, custom testing strategy. We choose the ideal approach for your application and select the best-fit testing tools. We’ll also provide feedback to inform the testing process and improve software quality.
Comprehensive Testing Coverage and Services
Our QA engineers and testers are experts in numerous testing approaches, methodologies, and services. We perform functional and performance testing, including security, stress, and usability testing. We also leverage manual and automated approaches for maximum test coverage and high-quality software.
Our process. Simple, seamless, streamlined.
Step 1
Discuss your requirements.
We’ll discuss your business goals, budget, timeline, and need for quality assurance services. During this initial call, we’ll determine if you need a dedicated software development team or one of our other engagement models.
Step 2
Create a plan and assemble a team.
We’ll craft a plan outlining our approach to QA testing, based on your requirements and engagement model. We’ll also assemble your team of QA specialists.
Step 3
Get to work.
Our QA engineers and testers will get to work. Throughout the software testing process, we will track metrics and keep you informed about our progress to ensure you stay up to date.
Frequently Asked Questions (FAQ)
Data science involves extracting insights from complex and unstructured data, using various statistical, mathematical, and programming techniques. For businesses, this translates into more informed decisions, enhanced business strategies, improved customer experiences, and more.
A data scientist takes your complex business challenges and formulates analytical solutions. They use data manipulation, statistical methods, and machine learning. By analyzing and interpreting complex datasets, they’ll help you make data-driven decisions. They can also provide actionable insights that are critical to your business strategies.
Data security is paramount to our operations. We employ advanced security protocols, encryption techniques, and compliance practices to ensure your data is securely handled, processed, and stored, safeguarding it from unauthorized access and data breaches.
Yes, our data science team can build tailored solutions. Whether you’re a startup, an SME, or a large enterprise, our robust data and analytics capabilities ensure the final solution aligns with your business objectives.
Artificial intelligence (AI) complements data science by automating data analysis processes, enabling more rapid and useful insights. AI learns from your data and improves data analysis by making predictions, recognizing patterns, and enhancing decision-making.
Looking for efficient Data Science Services? See how we can help.