Data Science

Data Science ServicesDecipher 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.

500+ companies rely on our top 1% tech talent.

Data Science Services We Provide

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.

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.

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.

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.

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.

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.

ENGAGEMENT MODELS

HOW WE HELP

Key Facts about Data Science Services

The Main Reasons for Outsourcing

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.

Why data science is so important

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.

Different types of analytics solutions we deliver

1. Descriptive Analytics: Analyzing historical data to understand factors that impacted past performance.

2. Predictive Analytics: Utilizing statistical and machine learning models to predict future events and trends based on historical data.

3. Prescriptive Analytics: Developing models to suggest actions you can take to affect desired outcomes before they happen.

4. Diagnostic Analytics: Examining data to understand the causes of past events and leveraging this information to improve future performance.

5. Decision Analytics: Employing data to support decision-making processes and determine future actions.

6. Real-time Analytics: Analyzing data as it's created in real-time to provide instant insights and facilitate immediate decision-making.

7. Customer Analytics: Utilizing data to understand customer behavior and trends, thereby informing strategies focused on customer retention and experience.

8. Fraud and Risk Analytics: Implementing models and algorithms to identify potentially fraudulent activities and assess various types of risk.

9. Supply Chain Analytics: Analyzing supply chain data to optimize and enhance logistics, production, inventory management, and distribution.

10. Text and Sentiment Analytics: Employing NLP and machine learning to analyze textual data and extract insights related to customer sentiments and trends.

11. Competitive Analytics: Analyzing data related to competitors and market trends to inform strategic planning and maintain a competitive edge.

12. Visual Analytics: Utilizing visualization tools to represent data graphically, enabling users to identify patterns, trends, and insights.

Our experts have been working alongside in-house teams for over a decade.

React
Angular
Node.js
Java
C++
.NET
Vue.js
JavaScript
Python
Golang
React
Angular
Node.js
Java
C++
.NET
Vue.js
JavaScript
Python
Golang

Swift
Figma
Adobe
C#
PHP
iOS
Android
Python
WordPress
Swift
Figma
Adobe
C#
PHP
iOS
Android
Python
WordPress

How to start with Us

Our process. Simple, seamless, streamlined.

Step 1
Join exploration call.

Tell us more about your business on a discovery call. We’ll discuss team structure and approach, success criteria, timescale, budget, and required skill sets to see how we can help.

Step 2
Discuss solution and team structure.

In a matter of days, we will finalize your project specifications, agree on an engagement model, select and onboard your team.

Step 3
Get started and track performance.

Once we’ve agreed on milestones, we’ll immediately get to work. We’ll track progress, report updates, and continuously adapt to your needs.

Frequently Asked Questions (FAQ)

What exactly is data science and how would it benefit my business?

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.

What is the role of a data scientist?

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.

How secure is my enterprise data when outsourcing data science services?

Can your data science service be customized to my business?

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.

How do your data science services leverage AI?

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.