PhD student, Postdoc, Professor. If you've spent some time in academia, you are very familiar with each of these roles and differences in responsibilities. For many people transitioning to Data Science, the number of role titles in this field is overwhelming. Unfortunately, providing an accurate guide in DS-related professions is impossible because every company has its idea of naming the roles. However, there are some generic things, which is good to know to find a role, that fits your strengths and interests the best (or to google which skills you might be missing to get such a job).
1. Data Scientist:
Data scientists specialize in making models from large datasets for some kind of automatisation. E.g. predict future demand based on historical sales, find defective parts during manufacturing based on pictures of good quality parts, predict churn probability for users of an app, etc. Good knowledge of ML, statistical analysis, and data visualization is a must. Academics find this role particularly appealing, as it allows them to apply their skills to solve real-world problems in various industries from healthcare up to finance.
However, the number of pure Data Scientist positions is quite limited. During the recession, most companies won't even consider candidates without any prior experience in their industry for this role.
2. Data Analyst:
Data analysts play a crucial role in transforming data into actionable insights. They often work closely with business stakeholders to identify trends, patterns, and opportunities. Academics transitioning into data analysis roles can leverage their strong analytical and communication skills to bridge the gap between data and decision-makers.
3. Business Intelligence (BI) Analyst:
BI analysts are close to Data Analysts, but with more focus on creating informative reports, dashboards, and visualizations to help businesses make data-driven decisions. This role could be a great fit if you enjoy translating data into easily digestible insights. Academics excel in this position due to their ability to distill complex information.
4. Machine Learning Engineer:
If you have experience developing algorithms, models, or simulations in academia, a role as a machine learning engineer may be a great fit. Machine learning engineers design and implement machine learning systems that power various applications, such as recommendation systems, autonomous vehicles, and natural language processing.
5. Data Engineer:
Data engineers are responsible for building and maintaining the infrastructure that enables data collection, storage, and processing. This role could be a good match if you have experience managing databases, ETL (Extract, Transform, Load) processes, and data pipelines. Data engineers are essential for ensuring data quality and accessibility within organizations.
6. Research Scientist (Applied Research):
For academics who enjoy the research aspect of academia, a career as a research scientist in data science can be a natural progression. In this role, you can work on cutting-edge research projects, collaborate with cross-functional teams, and apply your domain expertise to solve complex problems. Although responsibility-wise it sounds very familiar, getting such a job is much more difficult than a postdoc position and requires serious and tailored preparation.
7. Product Manager (Data-Driven Products):
Product managers in data-driven industries are pivotal in defining product strategies, identifying market opportunities, and overseeing the development of data-centric products or features. If you never liked coding, but enjoy taking up leadership and possess good communication skills you will excel in this job.
8. Data Science Consultant:
Working as a data science consultant can be an exciting option for those who prefer a varied and challenging career. Consultants assist organizations in solving specific data-related challenges, providing recommendations, and implementing solutions tailored to the client's needs.
In Germany a significant portion of data science related jobs are offered by consulting companies, names of which you probably never heard before. It might be a good place to gain experience in various domains in a short time, so do check it out ;)
Even if you know the right role for you, a job search might be overwhelming. If you need support, check out my "Job search empowerment" program. It's 6 weeks of personal 1:1 mentoring for people looking for a job in the Data field. Booking page
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