- CAREER OPPORTUNITIES
- SKILL SETS
- ROLES & RESPONSIBILITY
Data Science is a detailed study of the flow of information from the colossal amounts of data present in an organization’s repository. It involves obtaining meaningful insights from raw and unstructured data which is processed through analytical, programming, and business skills.
Data Scientist is the specialist who uses Mathematical and Statistical methods, computer modelling and software to extract knowledge and information from structured (Such as MS – Excel or SQL) or unstructured data .
How to be a Data Scientist
Bachelor in Science Information Technology (B.Sc. or B.Tech) or B.Sc in Computer Science/IT/Computer Application/Software Engineering/Mathematics/Statistics.
You should also study online courses in programming software like Python and Hadoop.
Postgraduate degree helps in getting better jobs and making more money. You can pursue a Diploma in Data Science (PGDDS), a full-time Post Graduate program in Data Science Business Analytics and Big Data (PGP-BA-BigData), or a Masters in Data Science (MS).
- Business Intelligence Analyst
- Data Mining Engineering
- Data Architect
- Technical Skills
- Analytical Skills
- Open Mindedness
- Decision making Skills
- Supervisory Skills
- Data scientist Skills
- R Programming
- Python Coding
- Hadoop Platform
- SQL Database/Coding
- Machine Learning and AI
- Data Visualization
- Unstructured Data
- Experience with major web services, including S3, Spark, Redshift, etc.
- Impulse to learn and master new technologies
- Good communication skills to promote cross-team collaboration.
- A natural inclination toward solving complex problems
- Experience using and developing data architectures
- Knowledge of Machine Learning techniques
- Verbal and Written communication Skills
- Programming and Technical Proficiencies
- Class XII Science stream with PCM
- Data warehousing/Data Engineering Expert
- Data Mining expert
- Database Management system expert
- Data Scientist(Predictive and Prescriptive Modeling)
- Data scientist(Machine Learning expert)
- Identify valuable data sources and automate collection processes
- Undertake preprocessing of structured and unstructured data
- Analyze large amounts of information to discover trends and patterns.
- Build predictive models and machine-learning algorithms.
- Combine models through ensemble modeling.
- Present information using data visualization.
- Work with stakeholders to determine how to use business data for valuable business solutions.
- Search for ways to get new data sources and assess their accuracy
- Browse and analyze enterprise databases to simplify and improve product development, marketing techniques, and business processes.
- Create custom data models and algorithms.
- Use predictive models to improve customer experience, ad targeting, revenue generation, and more.
- Develop the organization’s test model quality and A/B testing framework
- Coordinate with various technical/functional teams to implement models and monitor results
- Develop processes, techniques, and tools to analyze and monitor model performance while ensuring data accuracy