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How To Transition To A Career In Data Science? - Check Detailed Guide

Jul 8, 2023 | 6 minutes |

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One of the most prevailing concerns among professionals considering a career change to Data Science is “Do I need a technical background to enter the field?” The answer is a definite no. Having said that, you will need to hone in on some fundamental coding and mathematics. So, why do you have to pursue your dream job as Data Scientist? What are the skills recruiters are looking for in a candidate? The better question would be how do you do it? Back in the 1990s, computer engineers and Wall Street "quants" were in high demand. Today, organizations are competing to hire Data Scientists. As businesses grapple with enormous volumes and types of data, demand for these professionals has outpaced supply with a massive hike of 650%, far outpacing other sectors. Therefore, a transition to Data Science is undoubtedly a smart move.

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Despite the enticing and seemingly unlimited amount of options in data science, transitioning to data science might be challenging if you've already committed years of blood, sweat, and tears to another career path. There are, thankfully, ways to make the transition into a data science career considerably easier. Transitioning to Data Science is a smart move as it fetches far higher comparative returns! Source: India Today From the above chart, we can see that transitioning from a marketing analytics job to a data science job leads to a 37% salary growth on average & can go up to 120% for experienced professionals. Similar to this, a 31% on average salary growth is anticipated when workers move from digital analytics to data science. The pay increase might be as much as 44% for someone switching from a data engineering position to a data science position.

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Here are some steps that you can take to enter the sexist job of the 21st century! A mathematical model is the basis of the majority of AI and ML algorithms. In addition, an understanding of probability and statistics is necessary for statistical analysis and model evaluation. Therefore, it's great if you review these abilities to get the most out of data science. For a data scientist to succeed, being able to explain technical concepts to both non-technical and technical audiences is essential. If you can't communicate your model to others and persuade them to adopt and believe it, all the effort you put into developing the most precise model will be for naught. Excel is a pretty good starting point. Data science does, however, require familiarity with Python or R programming. It's preferable if you also learn how to use SQL to manipulate and query databases in addition to this. Data science involves the capacity to address challenges using innovative and logical thinking. To improve your problem-solving abilities, try putting some Kaggle tasks into practice. Learning how to use Data Visualization tools is one of the smart moves you can make! Power BI can be a great tool to start with. Take on a data science position that enables you to use your current abilities and allows you to expand your understanding of the new field. Keep an open mind to new chances and endeavors to put whatever data science-related abilities you have acquired to use. A certificate can increase your annual earnings by anywhere between 13 and 25%, according to Forbes. As a result, dedicating just 4-5 hours per week to gaining expertise in Data Science and Machine Learning will yield compounding benefits over time, enabling workers to broaden their employment options.  Note: Only 5 Seats Left in AltUni's Certificate Program in Data Science, where you get to land your dream job by paying only 25% of the Program Fee Upfront & remaining 75% only if you get placed! Hiring managers seek several key traits to hire a potential candidate, so, what are the characteristics that they look for in a data scientist? According to the experts, the best Data Scientists are All the data in the world won’t amount to much if the professional analyzing it lacks technical skills & doesn’t know his/her way around the data tool. Another essential quality is the capacity to confidently synthesize and manipulate a variety of data sets is demonstrated by having a strong foundation in mathematics and statistics. Data scientists never stop learning, especially when they work in a highly technological industry where new tools are always being developed and existing ones are being enhanced. One way to stand out is to recognize issues within the company or preferred remedies while also coming up with your own. Regardless of the position, they should challenge anything that seems ineffective to them.  Keeping up with the recent developments in the industry & speaking with the stakeholders to determine their pain spots is the best course of action. Although being able to code is one of the requirements for any Data Scientist, it is also crucial to comprehend and apply code to the business and its objectives. You can code more effectively if you fully understand the task at hand and how it relates to the business. Data scientists inspire innovation throughout organizations. One candidate may stand out among the others due to their inherent curiosity, excitement, and capacity to turn data into a product.

With AltUni’s Certificate Program in Data Science, we are bringing you a unique journey of getting upskilled & 100% placement assistance. You sure know that it takes 8-12 months to get into this ever-growing & most lucrative field of Data Science. AltUni assures you are skilled & job-ready within the span of 10 months.

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