Jobs in Tech 101
Data science professionals enjoy extensively thinking about solving abstract problems about data and technology. To do so, they must also show a strong interest in computer science, math, and in ongoing education and research to continue to stay up to date in the field. Data science professionals are curious and voracious learners, and have a natural ability to share and simplify.
Data scientists design and construct new processes for data modeling and production using prototypes, algorithms, predictive models, and custom analysis. They take an enormous mass of messy data points (unstructured and structured) and use their formidable skills in math, statistics and programming to clean, manage and organize them.
Data engineers build massive reservoirs for big data. They develop, construct, test and maintain architectures such as databases and large-scale data processing systems.
Machine learning engineers typically have stronger software engineering skills than data scientists and work with engineers to maintain production systems. They often code the algorithms provided by data scientists into the production system.
Meet with the customer success team to get feedback about a new product issue we can help solve
Prepare a visual analysis to explain a new language process my team created for our product
Start coding to perform and automate statistical analyses
Continue coding in a quiet environment to allow for focused work
Engage with my manager for a review of my code and process development
Wrap up the day by reading a recent article on new data science methodologies
Luke Zhang loves to solve problems with data. Read about why he chose Indy for his data science career.Read More
Zachary says nothing is more exciting than finding an elegant answer to a difficult problem. Read about his career in tech from IT analyst to data scientist.Read More
Ten years ago, I left Indianapolis in pursuit of a dream to join the most cutting-edge team I could possibly find. That search led me to Chicago, London, and back again. Along the way I worked with brilliant people, implemented cutting-edge technologies, and had some tremendous success. The journey has now brought me and my family back to Indianapolis where I plan to utilize all I have learned in order to create a world-class data science team at High Alpha.Read More
An undergraduate or graduate degree in Math, Statistics, Computer Science, or another quantitative discipline is usually required. Coursework in Linear Algebra, Calculus, Probability, Discrete Mathematics, Graph Theory, Statistical Modeling, Bayesian Analysis, Time Series Analysis, Data Structures and Algorithms, Numerical Methods, Machine Learning, and Data Mining is encouraged.
Product development professionals love building products, automating inefficiencies, and solving problems.
Data scientist professionals enjoy extensive thinking about data and abstract problems.
Designers are passionate about crafting beautiful, functional user experiences.
IT and cybersecurity professionals build and maintain the security of complex computer networks and databases.
Customer success professionals enjoy building relationships, and take pride in being the voice of the customer.
Support professionals have respect for all clients and team members, and enjoy engaging with people via phone and email to help them solve problems.
Sales professionals have a will to win and a knack for influencing and building relationships with people.
Marketing professionals crafting communications or experiences that inspire, inform, and influence people.
Finance managers have a passion for working with financial data and interpreting how a business makes money.
HR & office administration professionals have a passion for making sure the workplace is functional, comfortable, and efficient.