DATA SCIENCE ANALYST SKILLS, EXPERIENCE, AND JOB REQUIREMENTS

Published: October 4, 2024 - The Data Science Analyst identifies complex problems and formulates hypotheses to develop data-driven solutions through thorough analysis. Proficiency in statistical principles and advanced data models, such as classification and linear regression, aids in deriving insights for informed decision-making. Experience in connected vehicle solutions and a solid understanding of commercial vehicle transportation business models contribute to creating technical product requirements for IoT scale software solutions, enhancing profitability and efficiency.

Essential Hard and Soft Skills for a Standout Data Science Analyst Resume
  • Statistical Analysis
  • Data Visualization
  • Machine Learning
  • Python Programming
  • SQL
  • Data Mining
  • Big Data Tools
  • Predictive Modeling
  • Data Cleaning
  • Database Management
  • Critical Thinking
  • Problem Solving
  • Communication
  • Collaboration
  • Adaptability
  • Attention to Detail
  • Time Management
  • Continuous Learning
  • Interpersonal Skills
  • Presentation Skills

Summary of Data Science Analyst Knowledge and Qualifications on Resume

1. BS in Engineering with 2 years of Experience

  • Experience with healthcare data and API development and management
  • Expertise with Python, C#, C++, and ability to learn new coding languages 
  • Excellent verbal communication skills, organization, prioritization skills, and ability to learn quickly and work independently
  • Curious mindset and passion for problem-solving and experimentation
  • Mathematical, statistical knowledge, proficient computing skills using R and Python, T-SQL, Azure ML Studio, Hadoop-based tools
  • Superior multi-tasking skills and the ability to work in a fast-paced, often deadline-oriented and dynamic environment.
  • Self-starter who can work independently and be a strong team player
  • Hands-on data mining experience with both statistical and machine learning.

2. BS in Operations Research with 3 years of Experience

  • Strong communication skill, willing to collaborate with different parties
  • Deep understanding of Machine Learning concepts and algorithms (e.g. predictive modeling, clustering, NLP, Computer Vision, etc)
  • Good programming skills: Python (must), SQL (must), R
  • Experience in working on Data Science projects and building machine learning models, e.g. random forest, gradient boosting, LSTM, Bert, etc
  • Some experience as data scientist/data analyst intern before
  • Knowledge of insurance or financial services 
  • Familiar with visualization tools, e.g. Power BI, Tableau
  • Experience in any cloud platform is a plus, e.g. Azure, AWS
  • Well-organized, problem solver & fast learner
  • Good team player, efficient with minimal mistake tolerance
  • Good command of business English, both in written and spoken form

3. BS in Business Analytics with 5 years of Experience

  • Working experience in a quantitative field, preferred Financial/Credit Card industry
  • Familiar with revenue drivers for the cards business
  • Demonstrated ability in data retrieving and manipulation as well as proficient analytical skills
  • Excellent analytic ability and problem solving skills
  • Proficient in Microsoft Office including excellent MS Excel skills in developing analytic presentations
  • Excellent communication and interpersonal skills, be organized, detail oriented, and adaptive to matrix work environment
  • Hands-on experience in predictive modeling and analysis
  • Strong skills in problem solving, programming and computer science fundamentals
  • Experience with data science and big data
  • Experience in Computational Advertising

4. BS in Information Technology with 7 years of Experience

  • Experience working with large datasets from enterprise big data environments (Hadoop HBASE, Spark, Databricks, etc) 
  • Well developed critical thinking skills to identify a complex problem, formulate a hypothesis, and perform analysis to develop a solution 
  • A deep understanding of statistical principles and analysis 
  • Experience in connected vehicle solutions
  • Understanding of commercial vehicle transportation business models and associated factors (uptime, efficiency, etc) that contribute to profitability 
  • Experience with agile software development methodology and tools 
  • Experience formulating and creating technical product requirements for IoT scale software solutions 
  • Excellent interpersonal communication and expert presentation skills 
  • Understanding of advanced data models such as classification, linear regression, etc. and how to implement them 
Relevant Information
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