Data Scientist

_**Position Offered: Data Scientist**_
- **Location: Gandhinagar, Gujarat**_
- **What We do**:_

CereBulb transforms organizations by empowering people with data, streamlining process with technology in their digital transformation. CereBulb uses its experience and extensive knowledge of Enterprise Solutions such as Industrial Internet of Things, Industry 4.0 & Smart Manufacturing to accelerate our journey to success. CereBulb helps constructively from strategy building, change management and implementation of the disruptive AI based solution in various industries to lower operating and owning cost of the operation. As an industry leading solution integrator CereBulb serves Chemical, Power (Solar, Wind, Thermal, Hydro), Pharma, Manufacturing, Oil & Gas, IT & Telecom, Automotive, Energy, Metals & Mining verticals.
- **Required Technical and Professional Expertise**_
- Bachelor’s or master’s degree in a quantitative field (e.g., Computer Science, Data Science, Electrical Engineering, or related field).
- Strong knowledge of statistical analysis, machine learning algorithms, Time series modelling-forecasting, anomaly detection and predictive modeling techniques.
- Proficiency in programming languages such as Python or R, as well as experience with relevant data science libraries and frameworks.
- Experience with industrial data analysis and familiarity with industrial processes and systems.
- Knowledge of data historians, such as the PI server, and experience working with industrial data infrastructure.
- Ability to preprocess and integrate industrial data from various sources and formats.
- Familiarity with model deployment techniques and platforms, including deployment on the PI server or similar systems.
- Experience in optimizing industrial processes using data-driven insights and models.
- Strong data visualization and communication skills, including the ability to create clear and effective visualizations and reports.
- Knowledge of data privacy, security, and compliance considerations in the industrial domain.
- Knowledge of MLOps will be added advantage.
- Excellent problem-solving, analytical, and teamwork skills.
- Continuous learning mindset to stay updated with the latest advancements in data science, machine learning, and industrial technologies.
- **Non-technical skills**:_
- Critical thinker and problem-solving skills
- Knows how to work with a team.
- Good time-management skills
- Great interpersonal and communication skills
- **What Work you could do as a Data Scientist**:_

**Industrial Data Analysis and Modeling**:

- Analyze and process industrial data collected from various sources, including sensors, machines, and production systems.
- Identify patterns, trends, and anomalies in the data to gain insights into operational efficiency, process optimization, and predictive maintenance.
- Develop statistical models, machine learning algorithms, and predictive models to solve specific industrial challenges.
- Collaborate with domain experts to understand the context and requirements of industrial processes.

**Data Preprocessing and Integration**:

- Clean and preprocess industrial data by handling missing values, outliers, and noise.
- Integrate data from different sources and formats to create a unified dataset for analysis and modeling.
- Transform and engineer features to capture relevant information and enhance model performance.
- Work with data historians, such as the PI server, to extract, store, and organize industrial data.

**Model Development and Deployment**:

- Optimize models for performance, accuracy, and scalability.
- Deploy models on the PI server or other relevant platforms for real-time or batch processing.
- Monitor and maintain deployed models to ensure their continued effectiveness and reliability.

**Industrial Process Optimization**:

- Collaborate with cross-functional teams, including engineers, operations personnel, and management, to identify opportunities for process optimization.
- Use data-driven insights and models to recommend improvements in efficiency, productivity, quality control, and energy consumption.
- Implement and evaluate experiments, control strategies, and algorithms to optimize industrial processes.
- Provide actionable recommendations based on data analysis and modeling results.

**Visualization and Reporting**:

- Create visualizations, dashboards, and reports to communicate analysis results and model performance to stakeholders.
- Present complex technical concepts and findings in a clear and concise manner to both technical and non-technical audiences.
- Collaborate with data visualization experts or use tools like Tableau or Power BI to create interactive and intuitive visualizations.
- Helping our employees grow their foundational skills
- Finding the job at CEREBULB: navigating our company with the potential for many careers by channelling an employee’s strengths and career aspirations
- Diversity of people: Diversity of thought driv