- Data Science and Machine Learning Roles in Startups
- Data Science and Machine Learning Roles in Big Tech
- Comparing Skills Required for Startups vs. Big Tech
- Career Growth and Learning Opportunities in Startups vs. Big Tech
- Work Environment and Culture in Startups vs. Big Tech
- Programs That Can Help You To Master Data Science
- Programs That Can Help You To Master Machine Learning
- Conclusion
- FAQs
In today’s job market, data science and machine learning are the industries in demand, with both startups and big tech companies actively searching for skilled individuals.
In fact, According to the U.S Bureau of Labour Statistics the global demand for data scientists is expected to grow by over 36% by 2033. And machine learning is also expected to grow by 36.08% between 2024 and 2030.
In this blog, you will get a deep dive into the different roles in data science and Machine Learning, the skills needed in these domains, and what it’s like to work in a startup versus a big tech company.
Data Science and Machine Learning Roles in Startups
Startups are the place of innovations, and for data science and machine learning enthusiasts, this means more skill development and broad exposure. In Startups, you might find positions like:
1. Data Scientist
A Data Scientist is responsible for handling end-to-end data solutions, in which they have freedom of choosing tools and approach on their own. They collect, process, and analyze data to provide actionable insights for product and business.
- Skills Needed: Proficiency in Python, SQL, and data visualization tools like Tableau, along with statistical strong knowledge, is required.
- Salary range: Typically, a data scientist earns between 8 LPA and 20 LPA in India.
2. Machine Learning Engineer
ML Engineers are responsible for building and deploying ML models to improve the performance of product and customer experience. In startups, ML engineers often handle the entire ML pipeline, from data preprocessing to model deployment.
- Skills Needed: Coding(Python, R), Understanding of ML algorithms, familiarity with cloud services(AWS, Google Cloud), and also real-time data handling.
- Salary range: In India, machine learning engineers earn between 6 LPA and 17.3 LPA.
3. Data Analyst
Data Analysts are responsible for Generating data-driven reports, trends visualizations, and assisting in strategic decision-making. Analysts in startups work closely with different teams, providing insights that shape marketing strategies, product and growth of the business.
- Skills Needed: Excel, SQL, Basic to intermediate knowledge of ML concepts, and strong communication skills to present the findings to non-technical audiences.
- Salary range: The typical salary for a data analyst ranges from 4 LPA to 10 LPA in India.
Checkout to free courses to get started with your learning:
- Python Free course
- SQL Free Course
- Data Visualization Free Course.
- Data Preprocessing Free Course.
- Machine Learning Algorithms Free Course.
Why Startups?
Startups give you exposure to a variety of projects, making them an excellent opportunity to learn and explore. In startups you have more responsibilities which makes your personal growth more feasible. If you thrive on innovation and flexibility, startups could be the perfect place for you.
Data Science and Machine Learning Roles in Big Tech
In big tech companies, most data science and ML roles are specialized, and they are divided very cleanly. Common roles include:
1. Data Scientist
Responsible for conducting in-depth analysis, building predictive models (for predictive analytics), and creating data strategies to support large-scale operations. Big tech companies usually offer data scientists access to large proprietary datasets.
- Skills Needed: Advanced knowledge of Python, R, SQL, big data frameworks (like Hadoop), and specialized tools like Apache Spark.
- Salary Range: For entry to mid-level roles, salaries often range from ₹10-18 lakh per annum, with senior roles reaching ₹30 lakh and above.
2. AI Research Scientist
Responsible for developing new algorithms and contributing to research in fields like NLP, computer vision, and deep learning. Almost all contemporary AI research scientists work on projects that extend existing technology further.
- Skills Needed: Background in mathematics or statistics, research-oriented problem-solving skills, and strong knowledge of deep learning frameworks (TensorFlow, PyTorch).
- Salary Range: ₹15-25 lakh per annum, with experienced professionals in high-demand areas earning even more.
3. Data Engineer
Responsible for designing and maintaining data infrastructure, also managing large-scale data processing, and ensuring data availability for analytics. Data engineers at big tech companies typically work with massive data sets and complex data pipelines.
- Skills Needed: Expertise in SQL, cloud platforms (AWS, Azure), big data frameworks, and data pipeline management.
- Salary Range: Generally ranges from ₹5-15 lakh per annum, with further growth potential based on experience and specialization.
4. Machine Learning Specialist
Responsible for designing, training, and fine-tuning ML models for specific company needs. ML specialists in big tech do collaboration projects with teams focused on high-impact ML applications, like recommendation engines or fraud detection.
- Skills Needed: Experience with ML frameworks, expertise in model optimization, and understanding of scalable ML architecture.
- Salary Range: Between ₹6-17 lakh per annum for early-career specialists, with senior roles offering even higher compensation.
Great Learning Data Science and ML programs are designed to equip you with the skills needed for these different roles. With the curriculum focused on Python, SQL commands, and big data, they are curated for both beginners and professionals looking to specialize in one or another role.
Also you can check out our free courses in data science and machine learning to learn at your own pace and with no cost.
- Introduction to Data Science Free Course.
- Python for Data Science Free Course.
- Big Data Frameworks Free Course.
- SQL for Data Science Free Course.
Comparing Skills Required for Startups vs. Big Tech
When it comes to skills, both demand specific and unique skill sets for different levels of experience you have. Lets see what skills are required if you are looking at a startup or big tech job.
For Startups
In startups, you will usually work on a versatile skill set because of an open and broad tech stack, with requirements changing quickly. Your skills will cover coding, data analysis, data visualization techniques, and basic ML knowledge.
When working in startups adaptability is the key, with that eagerness to learn quickly and having good implementation skills can give you an edge.
For Big Tech
In big tech companies, you will be required to have specialized knowledge in specific areas of domains, with a critical focus on big data frameworks or deep learning algorithms. You will also need to have collaborative skills to work effectively with a cross-functional team.
Working in big tech companies gives you a very deep insight into topics like machine learning and data science, with which you can become a professional who specializes in very specific areas.
Career Growth and Learning Opportunities in Startups vs. Big Tech
Career growth is the main concern for most of the working professionals and even for some fresh graduates too. Let’s see how working in both environments will affect your career progression in the long term.
- Startups: They offer rapid growth paths with a hands-on approach, giving you broad exposure to different projects and technologies. The learning curve is steep, but the experience is rewarding, as you are destined to become a leader and handle more responsibilities on your own that go beyond your official role.
- Big Tech: These companies provide a structured growth path, often with mentorship programs and access to premium resources. You will have a defined path for advancement, and the opportunity to move between teams can provide a diverse learning environment within a single organization.
Work Environment and Culture in Startups vs. Big Tech
The work environment plays a crucial role in employee development, and retention. If an organization’s work environment is great the employee is more likely to get things done, and will be able to put their 100% into the task.
Let’s see what environmental variables are in Startups and Big Tech:
- Startups: Agile, fast-paced, and flexible. Here, as with many startups, the culture is creative-driven, and the work environment is more informal. Your work-life balance might swing a little, but chances are you’ll have a direct impact on the future of the company.
- Big Tech: Routine, structured, and balanced. Roles are well-defined in big tech, and the environment is mostly stable. Big tech companies are recognized for putting forward the adage that it’s about work-life balance with benefits — well, empirical evidence shows this to a certain extent.
Programs That Can Help You To Master Data Science
1. Postgraduate Program in Data Science and Business analytics
This program is for those learners who are seeking a career switch in the domain of data science and analytics. This program is aligned with the most in-demand industry skills and contains the placement assistance you need to secure your next dream job.
- Program Highlights:
- 50% average salary hike.
- 3300+ hiring companies, to get your dream job.
- Industry-aligned curriculum which contains 600+ hours of learning content.
- More than 22 tools and languages are covered which include Python, R, SQL, seaborn, RStudio and many more.
- Hands-on learning with real-world case studies and projects.
- Get a prestigious Dual Certification from UT Austin & Great Lakes, which are among the top Universities.
- Mentors and Faculty from top universities and organizations, to solve your each and every problem.
- Dedicated program support, with placement assistance, resume building sessions, interview preparation, and profile reviews.
- How program helps professionals working in Startups
- By enrolling in this program you will be learning skills specific to data science which will help you to advance your career in a higher role. No matter if you are at a junior or senior level this will help you to get those advanced skills needed for your next big promotion or career switch.
- How program helps professionals working in Big Tech
- If you’re in a big tech company, you may not get much career growth since you’re only going to be a specialist in a particular domain or role. By learning cross-functional data science skills, this program breaks down those barriers, so you can take your skill set beyond where you are currently.
- Here you’ll learn how you can use advanced data analytics and machine learning techniques on other projects to gain the power to explore more possibilities, further your career’s trajectory to more advanced roles or new departments, and wield greater impact within the larger organization.
2. PG Program in Data Science and Engineering
Jumpstart your career in data science with this 9 month online data science course, which is designed for beginners and freshers in India. With this you will gain critical skills in Python, Tableau, SQL, Pandas and Numpy.
- Program Highlights:
- 9 months online program with flexibility of learning anytime, anywhere.
- 3300+ hiring companies, past 90 days placement stats(150 job offers, 1 new hiring process).
- After 3-4 years of program, average 17.45 LPA CTC, with 550% hike for experienced professionals, and 320% hike for freshers.
- 1:1 mentoring from industry experts.
- Dedicated placement drives, access to job boards, career assistance.
- Earn a Data Science certificate from Great Lakes, ranked among the top 10 business schools.
- How program helps professionals working in Startups
- This program is valuable to anyone who is a professional in startups because the skills you learn will enable you to add value to your work, whether that is valued in growth plans, or innovation and growth. Data science knowledge also lets you understand customer behavior, optimize products and take data driven decisions, all important if you are scaling a startup.
- These advanced skills can prepare you for leadership positions, regardless of whether you’re in a junior or senior role, and make you a strategic asset in fast paced environments, where agility and innovation are key.
- How program helps professionals working in Big Tech
- In big tech, usually you work in a very specific or specialized role. Through this program, you learn how to break the constraints in place, so that you have the data science skills to pursue cross functional opportunities.
- This will allow you to apply Data Science techniques across projects, gaining experience across new departments and increasing your leverage in your company, and gears you up for a promotion. A broader skill set can make you the stand out person you can be in such a competitive environment.
Programs That Can Help You To Master Machine Learning
1. PGP in Artificial Intelligence and Machine Learning
This program is for those individuals who are interested in learning about machine learning and artificial intelligence on a professional level. With this highly curated program you will be able to make the desired transition in your career.
- Program Highlights:
- Get a 360 degree understanding of AI and machine learning.
- 50% average salary hike, with 3300+ hiring companies.
- Exclusive access to the great learning job board.
- Live career mentorship with industry experts.
- Personalized resume and LinkedIn review.
- Flexible to learn anytime and anywhere.
- Earn a dual certification from Great Lakes and UT Austin.
- Weekly online mentorship sessions, networking opportunities with people of similar interests.
- Dedicated program support.
- How program helps professionals working in Startups
- With flexibility and with innovation key to the startup world, this programme compliments exactly what is needed and contributes directly to those goals. When you master AI and Machine learning skills , you can bring product development, customer experience, and operational optimization.
- The skills they give you allow you to impact, to make impactful decisions and add value to fast growing teams, and that’s how you’re going to get promoted to leadership roles, how you’re going to become more and more responsible within a startup environment.
- How program helps professionals working in Big Tech
- This program is good for the people who are already working across big tech to expand their expertise in anything outside a specific role. Once you’ve become an expert in AI and ML, you’ll be equipped to have an input in many types of projects such as predictive analytics or process automation, which can help you grow your career inside the company.
- By learning with these in demand skills, you’ll have the tools needed to tackle more advanced challenges, expand your capabilities, and create openings for upward mobility in the world of big tech.
2. PGP-Machine Learning
Elevate your expertise in machine learning with this comprehensive machine learning course. Learn cutting-edge skills and tools for transformative insights. With this program you can kickstart your excel journey of success.
- Program Highlights:
- 7 Months online program, gives flexibility for working professionals to learn anytime and anywhere.
- Average hike of 50%,. With 3300+ hiring companies.
- 7+ projects under the guidance of industry experts.
- Curriculum development for working professionals.
- Certification from Great Lakes Executive Learning.
- 20+ hands-on projects and exercises in 10+ domains.
- 20+ professors, 2500+ industry expert mentors and 2 awards winning faculty to teach.
- Weekly mentorship sessions, networking and program support.
- Access to curated jobs with placement and career assistance.
- How program helps professionals working in Startups
- In startup environments, the professionals more often than not do more than one role and Machine Learning in decision making, Customer insights, and Product development plays a direct role.
- In this program, you’ll learn to hone your versatile ML skills to optimize processes, analyze data efficiently, and scale as needed. You’ve earned this expertise and are prepared for leadership positions, strategic choices, and enormous contribution to innovation on a growing team.
- How program helps professionals working in Big Tech
- If you are a big tech professional, this program gives you the chance to start diversifying your skillset and crack through the domain limitations. And all the advanced ML techniques you’ll learn make it possible to take on huge, data intensive projects and enhance your contribution in much more than one role.
- The application of cross functional ML skills not only will let you make a difference in many departments, it will offer you the chance to perform outstanding tasks and place yourself for fastened career development in an effectively aggressive big tech surroundings.
Conclusion
But in the end, your choice between starting your own company and joining a big tech company is really just about your career goals. This is because if you love having variety, fast growth, and solving creative problems, then a startup could be the best fit for you. But if you’re looking for specialization, structure, and long-term growth, big tech is the better option.
To build those specific skills, and grow in your career you can check out the Data Science and ML program by Great Learning which offers you the industry-aligned curriculum, with hands-on projects, and capability of using and learning the top tools and languages used in data science and machine learning.
FAQs
A. Startups offer high exposure to diverse projects; you expand your knowledge in a fast-paced environment with multiple growth opportunities and a hands-on approach to directly influence product and strategy.
A. You can consider your work style and aspirations. If you prefer dynamic, multi-faceted roles than startup might be the right fit for you. If you value structure, deep specialization, and clear advancement opportunities then big tech might be a good fit for you.
A. For startups, you can focus on building a broad skill set(coding, analytics, communication, and more). For big tech companies, focus on mastering specific skills(like Tensorflow, SQL, Python, and many more) while gaining deep knowledge of every topic you go through. You can also check out data science courses online for great learning and exploration.