Data Science Services
Data science services help companies run experiments on their data in search of business insights. Geniobits renders data science consulting leveraging Machine Learning, Artificial Intelligence, and Deep Learning technologies to meet our clients’ most deliberate analytics needs.
What Our Data Science Services Include?
1) Business needs analysis.
- Outlining business objectives to meet with data science.
- Defining issues with the existing data science solution (if any).
- Deciding on data science deliverables.
2) Data preparation.
- Determining data source for data science.
- Data collection, transformation and cleansing.
- Choice of the optimal data science techniques and methods.
- Defining the criteria for the future ML model(s) evaluation.
- ML model development, training, testing and deployment.
- Data science insights ready for business use in the form of reports and dashboards.
- Custom ML-driven app for self-service use (optional).
- ML model integration into other applications (optional).
Use Cases Geniobits Covers with Data Science Services
Operational intelligence
Optimizing process performance due to detecting deviations and undesirable patterns and their root-cause analysis, performance prediction and forecasting.
Supply chain management
Optimizing supply chain management with reliable demand predictions, inventory optimization recommendations, supplier- and risk assessment.
Product quality
Proactively identifying the production process deviations affecting product quality and production process disruptions.
Customer personalization
Identifying customer behavior patterns and performing customer segmentation to build recommendation engines, design personalized services, etc.
Predictive maintenance
Monitoring machinery, identifying and reporting on patterns leading to pre-failure and failure states.
Customer churn
Identifying potential churners by building predictions based on customers’ behavior.
Image analysis
Minimizing human error with automated visual inspection, facial or emotion recognition, grading, and counting.
Financial risk management
Forecasting project earnings, evaluating financial risks, assessing a prospect’s creditworthiness.