Data scientists need to master certain skills to convey complex data insights effectively. Here, we have listed down the top data science skills that can empower passionate people who are already working in data science or looking for a job change. Let us first overview a data scientist’s role and how it adds value to the business.
Role of a Data Scientist
Data science is the application of science, mathematics, and statistics to find relevant insights from data. Data scientists need to work on finding meaningful solutions by using some simple as well as some very complicated methods. The input to this process is simply the data that business SMEs have collected. These data can be utilized to extract insights, plan for the future, forecast trends, and make informed critical business decisions to enhance business. This process is supported by cutting-edge technologies such as Data Mining, Machine Learning Algorithms, and AI.
The expectation from a data scientist is to deliver the value of the data. They build and execute various machine learning algorithms, statistical analysis, optimization, recommendation engines, or automated ranking systems. A data scientist takes such data from various sources; data goes through its cycle to reach a structure that can be accepted as an input to a data science model built. The model’s output is the value of the most used data by various business process experts. Skilled Data engineers help them to build a pipeline to extract, cleanse and consolidate that data.
Businesses can create predictive models to simulate different events through data science. Hence, they will predict the best possible outcome and prescribe relevant efforts to improve performance. Furthermore, by analyzing recurring metrics over time, an organization becomes more efficient at decision-making.
Top Skills Needed to be a Data Scientist
A data scientist should be an expert in statistics and fluent in programming languages such as Python or R. He should specialize in building quick ML models using standard ML tools and algorithms. There needs to be a clear understanding of data pipeline ingestion and data wrangling methods. A basic awareness of business domain knowledge would really add great value. Most data scientists also specialize in data visualization tools and various graphs, and plots. The most frequently used tools by data scientists are Python, R, SQL, Jupyter notebooks, AWS, Tableau, C/C++, TensorFlow, and No SQL.
Key-Value Addition of a Data Scientist:
- Help set short-term, mid-term as well as long-term goals.
- Identify the actual user data from the huge volume of data being collected on a daily basis.
- Deliver value of data for critical business decision-making.
- Predict future outcomes, opportunities, and leads.
- In some cases, the simulation models can even help predict critical metrics and their interdependent relationships and impact of crisis situations.
Roadmap to Sharpen Data Science Skills
Are you already working in the field of data science? then enhance your skills by following the tips mentioned below:
- Joining, participating, sharing, and continuous learning through the various Data Science communities available at a considerable scale.
- Participating and reviewing solutions in competitions by various communities.
- Reading, browsing, and contributing to the latest content on Data Science communities such as IBM or Reddit.
- There are many researchers and senior data scientists who post and share a lot of important information on platforms like LinkedIn, and DS blogs. Following them helps learn and build a network.
- Attending Webinars, Workshops, and Events to learn and meet peers.
- A few online courses also add a great deal to your skillset.
How to Improve Data Science Skills
The field of data science is expanding rapidly, and data scientists are in high demand. This is great news for anyone interested in breaking into the Big Data sector. Scientists that specialize in data analysis are in high demand because of their ability to use numerical data to solve practical problems and interpret organizational needs.
How to improve data science skills and become a successful data scientist? When looking for a new employee, most businesses and recruitment agencies rely heavily on tests of a candidate’s skills. In addition to technical proficiency, a successful data scientist will also exhibit personality traits. You can’t teach yourself all the knowledge and attributes they possess. Companies and recruiters are under increasing pressure to fill open positions successfully, and as a result, they are increasingly turning to AI and ML-based solutions.
Enroll in a Certification Program
The most challenging aspect of becoming a successful data scientist and earning a six-figure salary is acquiring the necessary expertise. The easiest way to get your foot in the door is to study up on the most cutting-edge methods being used. Online data science programs are available for those who are interested in advancing their education and launching a data science profession.
Listen More and Read More
Reading and understanding scholarly articles is one of the quickest ways to develop your data scientist abilities. Students who are interested can find a wealth of free eBooks and other online resources to help them learn the fundamentals. Students of data science can benefit greatly from using LinkedIn to network with professionals in the field and keep up with developments in the field.
Make Contributions to the Data Science Community
Realize the value of your personal ties. To advance your career, it is helpful to become familiar with influential people in your field and to keep an eye out for other professionals. Struggling to land the ideal gig?
Meeting a company representative at a Data Science event or conference could result in you receiving that offer. Career paths in Data Science are not uniform. As your knowledge and experience expand, you will likely find yourself shifting titles between Data Scientist, Data Analyst, and other common roles in the field of machine learning. Read up on the best data science blogs and articles from Medium, and other authoritative online sources. Reading other blogs might give you a new viewpoint and help you better understand a concept if you’re having trouble grasping it.
Starting your own blog and writing about data science is a great way to challenge yourself. It’s a terrific method to test Skills data scientists need and review material you already know. If you want to impress recruiters with your dedication to your work and thirst for knowledge, starting your own blog is a great way to do both.
Grow Your Data Science Skills with Communities
There are communities that help take your Data Science skills to a higher level. The most popular one is Kaggle. It is known to have more than 3 million users across the world. Kaggle allows users to share their own work, their data sets, their scripts, algorithms, and the approach taken to solve a particular problem. The other communities that publish relevant and recent content to master Data Science skills are:
- Quora Data Science
- Open Data Science
- Data Community DC
- IBM Data Community
- Data Science Association
- Data Science Central
- Dataquest – Slack Channel
- Deep Learning on Udacity – Slack Channel
Events Data Scientists look forward to:
These upcoming events on data science will give you the opportunity to learn from industry experts and upgrade your data science skills.
- Graph + AI Summit Fall 2021 – 5th October 2021
- UC Center for Business Analytics Data Science Symposium 2021 – 12th October 2021
- WSDM’22, The 15th ACM International WSDM Conference – 21st February 2022
- Data 2023
- ICDM 2022: 22th Industrial Conf. on Data Mining – 16th July 2022
Online Courses to Enhance your Data Science Skills
Many online platforms offer hands-on learning support and exposure to sharpen your data science skills. Among several, a few are listed below which can provide you with an extra edge:
- High-Dimensional Data Analysis – Harvard University
- MS in Data Science Programme – Northwestern University School of Professional Studies
- Data Science and Machine Learning: Making Data-Driven Decisions – MIT & IDSS
- The Data Science Course 2023: Complete Data Science Bootcamp – Udemy
- PG Program in Data Science & Engineering (Data Engineering Specialization) – Great Lakes Executive Learning
Explore exciting job openings in the field of data science, engineering, and analysis.
- Data scientists must find meaningful solutions using data collected from SMEs and other sources. These data can be used to extract plans for the future, trends of the forecast, and make critical business decisions to enhance business. Some technologies like data mining, AI, and machine learning algorithms support this process.
- Data scientists need to deliver the data value. Also, they must build and execute many types of machine learning algorithms, statistical analysis, etc.
- Data scientists need to come up with the best possible outcome to improve performance for that business to create predictive models for simulating different events by data science. Analyzing the metrics over time allows an organization to make itself more efficient at decision-making.
- High-Dimensional Data Analysis course at Harvard University.
- MS in Data Science Programme at Northern University, the School of Professional Studies.
- The PG program in Data Science and Engineering is a Data Engineering Specialization course at Great Lakes Executive Learning.
- The Data Science Course is a complete data science at Bootcamp- Udemy.
- Data Science and Machine Learning: Making data-driven decisions at MIT and IDSS.
- At a considerable scale, there are various data science communities; by joining those, you can participate, share and continuously learn.
- Also, you can participate in their computations and review the solutions through these various communities.
- There are many senior data scientists and researchers on various online platforms where they post and share a lot of important information, so you can follow them and their information through those online platforms to learn and build your network.
- It would help if you kept following, reading, and browsing all the latest data science content to keep updating yourself.
- To learn more, you can attend webinars, events, and workshops.
- Lastly, the online courses also add great value as they help update your skills.
