Data is the lifeblood of modern-day businesses. But just how valuable is it? In 2022, the market value of big data was $231.43 billion, and forecasts reveal that this value will peak at $549.73 billion by 2028. These figures underline the utility of data to businesses and why data professionals are in high demand.
For instance, data science ranks third among the best tech jobs. It also offers competitive salaries and opportunities for career advancement. Job portal Glassdoor states that entry-level data scientists in the US can earn an average salary of $75,888.
So, if you seek to launch a data career, it’s essential to know the required skills and relevant career paths in the field. Read on as we explore the various paths you can explore in the field of data and how you gain the necessary skill set in a sprint with the tech bootcamp, Le Wagon.
Le Wagon offers an online and in-person Data Science Bootcamp covering skills like data analysis, decision science, machine learning, and deep learning.
Learn more about Le Wagon’s Data Science Bootcamp.Top 9 Data Jobs to Pursue in 2022 with Le Wagon
Le Wagon is an industry-leading tech bootcamp where students girdle themselves with in-demand tech skills and real-world work experience to become business-ready tech professionals. Here are the top nine data jobs you can pursue with Le Wagon in 2022:
1. Data Analyst
- Average Salary: $62,789 (entry-level); $99,101 (senior-level)
What is a data analyst? Data analysts implement statistical methods to clean, process, and extract valuable information from data to drive business decisions. They check data quality, develop robust databases, and identify trends in complex data sets. Essential data analysis tools include Python, MySQL, Apache Spark, R, and Jenkins.
2. Machine Learning Engineer
- Average Salary: $110,071 (entry-level); $153,255 (senior-level)
What is a machine learning engineer? Machine learning (ML) is a branch of artificial intelligence (AI) that involves the development of applications and systems by utilizing data to predict outcomes with higher accuracy. ML engineers choose quality data sets, research and apply ML algorithms, and build functional ML systems. They use relevant ML tools like TensorFlow, Shogun, Sci-Kit Learn, and Apache MXNet.
3. Business Intelligence Analyst
- Average Salary: $72,481 (entry-level); $114,220 (senior-level)
What is a business intelligence analyst? Business intelligence (BI) analysts leverage tech tools to analyze data and provide deployable information to help businesses make smart decisions.
Their day-to-day responsibilities include identifying business requirements, creating business intelligence solutions, and delivering reports to managers and stakeholders. Some powerful BI tools are SAS BI, Microsoft Power BI, SAP Business Objects, and Datapine.
4. Data Scientist
- Average Salary: $68,054 (entry-level); $135,924 (senior-level)
What is a data scientist? Data scientists gather, process, and analyze big data to develop predictive models for optimizing business operations. Popular data science tools are SAS, Apache Spark, D3.js, and BigML.
5. Operations Analyst
- Average Salary: $67,000 (entry-level); $89,982 (senior-level)
What is an operations analyst? An operations analyst assesses a system’s performance and weighs it against operational parameters like downtime and cost. They then deliver reports with recommendations to improve the company’s operations. An operation analyst uses tools like BizTalk 360, Cisco DNA Spaces, and SingleStore to execute their tasks.
6. Marketing Analyst
- Average Salary: $41,000 (entry-level); $87,707(senior-level)
What is a marketing analyst? A marketing analyst identifies potential customers and available markets for successful product sales. Powerful marketing analytics tools are Google Analytics, MixPanel, Cyfe, Klipfolio, and SEMrush.
7. Quantitative Analyst
- Average Salary: $76,376 (entry-level); $114,704 (senior-level)
What is a quantitative analyst? A quantitative analyst, also called quant, specializes in providing risk management and financial solutions. They apply mathematical and statistical modeling to analyze behavior and business performance. A quant uses Excel, MATLAB, JMP, and SPSS for quantitative analysis.
8. Data Visualization Specialist
- Average Salary: $61,991 (entry-level); $91,904 (senior-level)
What is a data visualization specialist? A data visualization specialist designs and delivers visual representations of quantitative and qualitative data through graphs, charts, and maps to inform internal clients and stakeholders. Some top tools for data visualization are Google Charts, Chartist.js, Infogram, ChartBlocks, and Grafana.
9. Data Product Manager
- Average Salary: $107,882 (entry-level); $132,814 (senior-level)
What is a data product manager? Data product management specifically involves collecting, storing, organizing, and managing product data. A data product manager leverages market data to improve product development. They also utilize data science methods to customize and improve the product experience. Data product managers have deep knowledge and skill using MySQL, Python, and MixPanel.
If you’re wondering how you can start a career in any of the data roles above, there’s a path you can take that doesn’t require a degree, and offers practical training, along with comprehensive job search support. Enter, Le Wagon.
3 Reasons to Learn Data at Le Wagon Bootcamp
Le Wagon is a tech bootcamp that offers a Data Science program that’s accessible online and on-site as well as full-time or part-time on 36 campuses worldwide. As a result, learners can easily fit their training into their schedules, making this an ideal program for career starters and working professionals looking to upskill or switch careers.
That’s not all. Here are three reasons why you should enroll in Le Wagon’s Data Science program:
1. Learn from an industry-led curriculum.
Le Wagon tailors its curriculum to cover the most in-demand skills that employers seek, ensuring that students fill the skills shortage in the field. The Data Science curriculum splits into six phases, with the last one reserved for project-building.
The other phases tackle data analysis, decision science, machine learning, deep learning, and data engineering. Python, data visualization, SQL, unsupervised learning, neural networks, and MLflow are only a few of the tools and techniques you’ll learn throughout your training.
Behind Le Wagon’s Data Science curriculum are leading experts in data science and machine learning, namely:
- Sébastien Saunier, the CTO of Le Wagon with over 10 years of experience at Google and VirtuOz;
- Mathieu Ripert, Machine Learning Engineer at Instacart; and
- Igor Koval, a PhD holder in Deep Learning and works for the center of applied maths of Ecole Polytechnique and the research lab at Brain and Spine Institute
2. Be part of a global community of data professionals
Le Wagon’s Data Science program gives you access to its global community of over 15,000 alumni. From Day 1 of the bootcamp, Le Wagon organizes various events to build a sense of camaraderie among the students. Students can also communicate via Slack.
As a result, self-run communities formed by Le Wagon students are not unheard of. Members of these communities participate in fun activities together, including ski excursions, outings, and batch parties.
For many alumni, being a member of the Le Wagon global community goes beyond building friendships. It also extends to building professional networks. For instance, hundreds of alumni have met co-founders and employees of their tech startups at Le Wagon. As of 2022, several Le Wagon alumni have launched 200 startups that have raised over $808 million.
3. Access comprehensive career services for your job search.
Your training at Le Wagon does not end with learning the tools of the trade. Instead, Le Wagon equips you with four tools or resources designed to prepare you for your job search. These include:
- A career playbook that contains tips and tricks to optimize your job hunt experience;
- Career events to connect with prospective employers and build your network; career intros between you and Le Wagon’s hiring partners; and
- Alumni coaching sessions, where you get to hear how Le Wagon alumni used the skills they honed at the bootcamp to start their careers.
Alumni Interview: Is Le Wagon Worth It?
Le Wagon’s Data Science Bootcamp builds students into data professionals. Many of its graduates testify to this, recognizing how the bootcamp helped open new doors to better careers. Clementine Contat and Clement Chausserie-Lapree are among them.
Clementine Contat
Clementine Contat worked with data in the banking sector for some years. Afterward, she bagged an MBA and joined a startup, leading their product launch in international markets. As her knowledge of product grew, Clementine became interested in the engineering side of products.
“And someone told me about Le Wagon saying, ‘Oh, you should try that. It would be interesting to really understand what it’s like to code.'” So she did.
She found Le Wagon’s Data Science Bootcamp to be comprehensive. Data sourcing, data analysis, deep learning, machine learning, and data engineering were among the concepts discussed. This strengthened her understanding of what it means to train a machine learning algorithm.
Armed with a new skillset, Clementine jumpstarted her search for data science and machine learning roles. And because of her background, her scope of job prospects also stretched to product management. As a result, she received two job offers: one as a product manager and the other as a data analyst.
In the end, she went with the former and has not looked back since. Thanks to her training at Le Wagon, Clementine says she has no problem collaborating with data scientists.
“With data scientists, it’s a bit different. You need to understand what’s a model. You need to be able to speak to data scientists to understand what they say, to translate that to the business, and also to be able to challenge them on their decisions.”
So, what’s her advice to Le Wagon students? “Commit the time and energy to really focus on the program and learn as much as possible…It’s quite intense, but you’ll get a lot out of it if you put a lot into it.”
Clément Chausserie-Lapree
Clément Chausserie-Lapree worked in advertising for various agencies in London for six years. Throughout the years, he developed a keen interest in products, creating automation, and working closely with data engineers. With more experience, Clément wanted to test his potential as a data engineer.
And that’s when he joined Le Wagon’s Data Science Bootcamp. There, Clément spent long hours learning the fundamentals of data science, including related fields such as data analytics, machine learning, and data engineering.
His time at the bootcamp opened his eyes to the value of data skills, specifically in simplifying tasks that many people typically consider tedious or too complicated. “… Even in the first week [of Le Wagon Data Science course], I thought, ‘oh, if I had known that before, it would’ve been so useful… I could have done all that myself without waiting four weeks for a data engineer to be available…”
After completing his training, Clément became a teaching assistant at Le Wagon and eventually moved up to an instructor role. After accumulating further experience, he joined John Lewis, a home fashion retail company, as an Insights Manager. There, he works cross-functionally with the data engineering and marketing teams as he leverages his data skills to deliver insights that inform product development and marketing strategies.
“The impact it can have on the business is a really interesting aspect of working with data,” said Clément.
Kickstart Your Data Career with Le Wagon
As data becomes the top commodity among businesses worldwide, numerous opportunities are opening up for people who aspire to enter the field of data. But, to take advantage of these, you’ll need to build a solid foundation in data. And you can do so with Le Wagon’s Data Science program.
Are you ready to launch a data career? Enroll in Le Wagon’s Data Science program today.
About us: Career Karma is a platform designed to help job seekers find, research, and connect with job training programs to advance their careers. Learn about the CK publication.
