Data Science for Business

Delivering custom AI/ML solutions for faster and smarter insights

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Become a data driven enterprise and make better business decisions to gain competitive advantage

Businesses struggle to leverage two-third of the data available to them. Sigmoid’s data science services help enterprises create robust data strategies and deploy advanced ML and AI techniques to unlock hidden insights and explore new opportunities with data. We equip enterprises with measurable and objective success definitions for complex business goals and leverage data-driven decision frameworks and accelerators to deliver high impact on analytics initiatives.

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Faster and actionable insights for business

Data Science Services and Solutions

Embed advanced analytics into business strategy and reduce time to results across business functions. Sigmoid's data science consulting delivers advanced analytics solutions offering tangible results to business challenges by identifying the right problems and implementing the right tools and technologies in machine learning, artificial intelligence and deep learning. We have a team of highly competent data scientists and data professionals working to solve your problems.

Supply Chain Analytics

Get a scalable and holistic solution for supply chain teams to optimize inventory and mitigate business disruptions while improving forecast accuracy.

  • Demand forecasting
  • Inventory optimization
  • Stock analytics
  • Logistics route optimization
  • Supply chain management
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Marketing Analytics

Develop highly targeted marketing strategies that are scalable across brands and geographies.

  • Hyper-personalization
  • Multi-touch attribution
  • Social media analytics
  • Ecommerce campaign optimization
  • Predictive Analytics

Customer Analytics

Understand customer needs and improve the customer experience (CX) journey with our end-to-end customer analytics solutions.

  • Customer lifetime value
  • 360 Customer journey
  • Sentiment analysis
  • Customer churn prevention
  • Customer experience personalization

Expertise across the data science techniques and technology stack

Techniques:

  • Classification and clustering
  • Graph modeling
  • Geo-spatial analytics
  • Knowledge representation
  • Time series modeling
  • NLP
  • Image processing
  • Sensor analytics
  • Sequence mining
  • Natural Language Processing

Tech Stack:

Data Science Technology stack

BI and Data Visualization

Turn data into visual insights with automated and interactive enterprise grade BI platforms. Our real-time dashboards with high refresh rates are powered by robust data pipelines which ensure high quality insights and can quickly scale with changing data requirements. Our 6-step framework enables effective insights exploration across descriptive, preventive, predictive, and prescriptive analysis.

BI and Data Visualization
Accelerator

Campaign performance dashboards

Check out our multi-touch attribution platform with interactive dashboards for CPG marketers.

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Artificial Intelligence

Advanced and cutting edge techniques for creating insights from data to explore new opportunities and stay ahead of competition.

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NLP

Intelligent text extraction systems go beyond hashtags and mentions to detect early warning signs and alerts. Models like GPT 3 have paved the way for advances in sentiment extraction, language translation, text classification, and question-answer systems to revolutionize how businesses engage with customers.

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Computer Vision

Deep insights from raw and 3D images uncover digitization opportunities such as image and video analytics, facial recognition, crowd dynamics, and document analysis with custom, pre-trained SOTA models. These have transformed the way companies create experiences across real, VR, and AR environments.

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Quantum Computing

With the ability to convert scrupulous volumes of data into meaningful insights faster and more accurately, quantum computers solve the most complicated problems. Some of our innovative work include Quantum SVM for the classification of breast cancer, Quantum GAN for option pricing, and others.

Whitepaper

Maximizing on-shelf availability (OSA) for CPGs with machine learning

Find out how CPGs can leverage data and analytics to identify inventory compliance gaps in the retailer network, and improve sell-out.

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Customer success stories

Explore our other data and analytics offerings

Data strategy

Build a robust analytics roadmap and modernize your data fabric for driving business transformation.

Data engineering

Drive higher business outcomes by operationalizing AI platforms and improving the efficiency of data pipelines on cloud.

Accelerators

Leverage our pre-built analytics assets and proprietary frameworks to accelerate data-to-value for your business.

Insights and perspectives

Blog Increased CLTV through personalization

Increased profitability and customer lifetime value through personalization

Podcast Marketing analytics for CPG

Multi-touch attribution to drive ROI with real-time marketing measurement

Point Of View Supply chain analytics for consumer good

Demand forecasting and supply chain analytics for consumer goods

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Level up your AI and ML initiatives to deliver a winning business strategy.

FAQs

Data science is the application of statistical and computational techniques to the extraction of insights from data. AI is a subfield of computer science that entails the creation of algorithms capable of performing tasks that ordinarily demand human intelligence. Data science is related to AI because it provides the data and insights used by AI algorithms for learning and decision-making.

Data scientists help businesses in making decisions based on data. Large datasets are mined for insights using statistical analysis, machine learning algorithms, and data visualization tools. These insights may be utilized to enhance business operations, optimize marketing campaigns, and create new products. Data scientists also assist businesses functions in identifying new data sources and developing data collection and management strategies. They collaborate closely with data engineers and analysts to ensure that data is accurate, trustworthy, and accessible.

While traditional statistics and data analysis methods have been used to explain and predict, data science takes this further to process the data to drive deeper actionable insights. It has been used across various industries to solve business problems such as planning out a customer acquisition and retention strategy, defining the supply chain analytics, predictive analytics, enabling marketers to measure and optimize marketing tactics, and more.

Sigmoid is a leading data solutions company with core specialization in data engineering, data science, and AI solutions. Sigmoid has developed expertise in handling end-to-end machine learning projects, deploying ML models into production, implementing AI use cases and more. Sigmoid sets itself apart from its competitors by delivering tangible business outcomes for problems leveraging data while traditional software services firms and internal data science teams struggle, such as putting ML models into production. The Data Science team at Sigmoid is built on five pillars — talent, cutting-edge technology training, problem-solving capabilities, innovation, and impeccable execution. The company has built analytics solutions for use cases across industries like CPG, pharma, insurance, AdTech, and manufacturing.

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