Data Scientist Salary, Skills, Jobs And Resume | Data Scientist Career | Data Science | Simplilearn
This presentation about "Data Science Engineer Career, Salary, and Resume" will help you understand who is a Data Science Engineer, the salary of a Data Science Engineer, Data Science Engineer Skillset and Data Science Engineer Resume. Data science is a systematic way to analyze a massive amount of data and extract information from them. Data Science can answer a lot of questions, as well. Data Science is mainly required for better decision making, predictive analysis, and pattern recognition. Below are topics that we will be discussing in this presentation: 1. Introduction to Data Science 2. Who is a Data Science Engineer 3. Data Science Engineer Skillset 4. Data Science Engineer job roles 5. Data Science Engineer salary trends 6. Data Science Engineer Resume Why learn Data Science? Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. The data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data, you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data. You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to: 1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics. Install the required Python environment and other auxiliary tools and libraries 2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions 3. Perform high-level mathematical computing using the NumPy package and its large library of mathematical functions Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave 4. Perform data analysis and manipulation using data structures and tools provided in the Pandas package 5. Gain expertise in machine learning using the Scikit-Learn package Data Science with python is recommended for: 1. Analytics professionals who want to work with Python 2. Software professionals looking to get into the field of analytics 3. IT professionals interested in pursuing a career in analytics 4. Graduates looking to build a career in analytics and data science Learn more at https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training
Data Scientist Salary, Skills, Jobs And Resume | Data Scientist Career | Data Science | Simplilearn
- 2. What’s in it for you? 1. Introduction to Data Science
- 3. What’s in it for you? 1. Introduction to Data Science 2. Who is a Data Science Engineer
- 4. What’s in it for you? 1. Introduction to Data Science 2. Who is a Data Science Engineer 3. Data Science Engineer skillset
- 5. What’s in it for you? 1. Introduction to Data Science 2. Who is a Data Science Engineer 3. Data Science Engineer skillset 4. Data Science Engineer job roles
- 6. What’s in it for you? 1. Introduction to Data Science 2. Who is a Data Science Engineer 3. Data Science Engineer skillset 4. Data Science Engineer job roles 5. Data Science Engineer salary trends
- 7. What’s in it for you? 1. Introduction to Data Science 2. Who is a Data Science Engineer 3. Data Science Engineer skillset 4. Data Science Engineer job roles 5. Data Science Engineer salary trends 6. Data Science Engineer resume
- 8. What does a Machine Learning Engineer do? Introduction to Data Science
- 9. Introduction to Data Science i Data science is a systematic way to analyze a massive amount of data and extract information from them
- 10. Introduction to Data Science Better Decision Making Either A or B? Predictive Analysis What will happen next? Pattern Recognition Is there any important hidden information in the pattern? Data Science is mainly needed for:
- 11. Which route will help me reach faster? 2 Introduction to Data Science Data Science can answer a lot of questions as well! How many viewers like the same movies? 1 Will this AC work for 3 years or fail earlier? Yes or No? 3 Who will win the World Cup? 4
- 12. What does a Machine Learning Engineer do? Who is a Data Science Engineer?
- 13. Who is a Data Science Engineer? A Data Science Engineer is someone who has
- 14. Who is a Data Science Engineer? Programming experience in Python and R (expert level knowledge). Ability to write proficient codes 1
- 15. Who is a Data Science Engineer? Strong SQL and big data experience. Strong coding skills with hands-on big data experience 2
- 16. Who is a Data Science Engineer? Ability to visualize models and troubleshoot code of the models 3
- 17. Who is a Data Science Engineer? Ability to visualize models and troubleshoot code of the models 3
- 18. Who is a Data Science Engineer? Versatile problem solver equipped with strong analytical and quantitative skills 4
- 19. Who is a Data Science Engineer? A self-starter with a strong sense of personal responsibility and a technical orientation 5
- 20. Who is a Data Science Engineer? Strong product intuition, data analysis skills, and business presentation skills 6
- 21. Who is a Data Science Engineer? Great teammate with excellent interpersonal skills 7
- 22. What does a Machine Learning Engineer do? Data Science Skillset
- 23. Big Data Data Science Engineer Skillset Database Knowledge Statistics Programming Tools Data Wrangling Data Visualization Machine Learning
- 24. Database Knowledge Tools required SQL (Structured Query Language) is an essential language for extracting a large amount of data from data sets. Knowledge of SQL is mandatory for Data Science Engineers Database Knowledge
- 25. Statistics Statistics Statistics is a subset of mathematics that deals with collecting, analyzing, and interpreting data. Therefore, data scientists need to know statistics Statistics Probability
- 26. Programming Tools Programming Tools Master any one of the specified programming languages. Programming Tools such as R, Python, SAS are essential to perform analytics in data Python is an open-source general purpose programming language Python libraries like NumPy and SciPy are used in Data Science SAS can mine, alter, manage, and retrieve data from a variety of sources Can perform statistical analysis on the data R is a free software environment for statistical computing and graphics Supports most Machine Learning algorithms for Data Analytics like regression, association, clustering, etc.
- 27. Data Wrangling Data Wrangling Data Wrangling is the process of transforming raw data into an appropriate format to make it useful for analytics Data Wrangling involves: Cleaning raw data Structuring raw data Enriching raw data
- 28. Machine Learning Machine Learning Knowledge of Machine learning techniques such as supervised machine learning, decision trees, linear regression, KNN, etc. is useful for few job roles KNN Linear Regression Decision Tree
- 29. Data Visualization Data Visualization Data visualization is the study and creation of a visual representation of data. Data visualization uses algoritms, statistical graphics, plots, information graphics and other tools to communicate information clearly and effectively
- 30. Big Data Big Data Big Data is a massive amount of data which cannot be stored and processed using traditional methods Big Data has various benefits like – • Access to social data can enable organizations to tune their business strategies • Big data can improve customer experience
- 31. Non Technical Skills Companies look for someone who can clearly and fluently translate technical findings to a non- technical team 3 A Data Science Engineer needs to work with everyone in the organization, including customers 4 Updating knowledge by reading contents and relevant books on trends in data science 1 Intellectual Curiosity Understanding how the problem solved can impact the business 2 Business Acumen Communication Skills Team Work
- 32. Non Technical Skills Companies look for someone who can clearly and fluently translate technical findings to a non- technical team 3 A Data Science Engineer needs to work with everyone in the organization, including customers 4 Updating knowledge by reading contents and relevant books on trends in data science 1 Intellectual Curiosity Understanding how the problem solved can impact the business 2 Business Acumen Communication Skills Team Work
- 33. Non Technical Skills Updating knowledge by reading contents and relevant books on trends in data science 1 A Data Science Engineer needs to work with everyone in the organization, including customers 4 Intellectual Curiosity Understanding how the problem solved can impact the business 2 Business Acumen Companies look for someone who can clearly and fluently translate technical findings to a non- technical team 3 Communication Skills Team Work
- 34. Non Technical Skills Updating knowledge by reading contents and relevant books on trends in data science 1 Companies look for someone who can clearly and fluently translate technical findings to a non- technical team 3 Intellectual Curiosity Understanding how the problem solved can impact the business 2 Business Acumen Communication Skills A Data Science Engineer needs to work with everyone in the organization, including customers 4 Team Work
- 35. What does a Machine Learning Engineer do? Data Science Job Roles
- 36. 1. Data Scientist Languages R, SAS, Python, MATLAB, SQL, Hive, Pig, Spark Companies hiring Data Scientists Perform predictive analysis and identify trend and patterns that can help in better decision making Role Understanding challenges of a system and offer best solutions
- 37. 2. Data Analyst Languages R, Python, JavaScript, HTML, C/C++,SQL Role Responsible for a variety of tasks such as visualization, optimization, and processing large amount of data Companies hiring Data Analysts Performs queries on database from time to time. Create and modify algorithms which can be used to reduce information from large databases
- 38. 3. Data Architect Languages SQL, XML, Hive, Pig, Spark Ensuring that data Engineers have best tools and systems to work with Role Creates blueprints for data management with the best security measures Companies hiring Data Architects
- 39. 4. Data Engineer Languages SQL, R, MATLAB, SAS,SPSS, Python, Java, Ruby, C++, Perl, Hive, Pig Updates the existing systems with better version of the current technologies to improve the efficiency of the databases Role Develops, constructs, tests and maintains architectures (such as databases and long-scale processing systems) Companies hiring Data Engineers
- 40. 5. Statistician Languages SQL, R, MATLAB, SAS, SPSS, Stata, Python, Perl, Hive, Pig, Spark Creates new methodologies for engineers to apply Role Extract and offer valuable reports from the data clusters through statistical theories and data organization Companies hiring Data Engineers
- 41. 6. Database Administrator Languages Java, SQL, Ruby on Rails, XML, C#, Python Role Ensures that all the databases are available to all relevant users, and is performing correctly and is being kept safe Some of the tasks involved are - Monitoring, operating and maintaining databases; Installation, configuration, defining schemas, training users, etc. Companies hiring Data Engineers
- 42. 7. Data and Analytics Manager Languages SQL, R, SAS, Java, Python, MATLAB Role Oversees the data science operations and assigns the duties to the team according to skills and expertise Improves business processes as an intermediary between business and IT Companies hiring Data Engineers
- 43. 8. Business Analytics Languages SQL Role Act as a link between the data engineers and the management executives. Possess specialized knowledge of their business domain, and apply that knowledge and analysis specifically to the operation of the business Companies hiring Data Engineers
- 44. What does a Machine Learning Engineer do? Data Science Engineer Salary Trends
- 45. Data Science Salary Trends In US, the average salary is $117,345/year Source - Glassdoor
- 46. Data Science Salary Trends In India, the average salary is ₹9,50,000/year Source - Glassdoor
- 47. Data Science Salary Trends National average salary for different job roles in data science Source - Glassdoor
- 48. Data Science Salary Trends Growth in Data Science job listings Source - Glassdoor
- 49. What does a Machine Learning Engineer do? Data Science Engineer Resume
- 50. Note- please show the resume