DATA ANALYTICS ASSOCIATE SKILLS, EXPERIENCE, AND JOB REQUIREMENTS
Updated: Mai 19, 2025 - The Data Analytics Associate has experience in data analytics across industry, academia, and financial services, showcasing strong proficiency in SQL (preferably T-SQL) and reporting tools such as PowerBI, SSRS, and Tableau. This role requires advanced skills in R and/or Python, along with a solid understanding of data analytics applications in a business context and the banking regulatory environment. The associate possesses excellent analytical and problem-solving abilities, along with effective communication skills to engage with senior management and stakeholders while maintaining a commitment to professionalism and integrity.
Essential Hard and Soft Skills for a Standout Data Analytics Associate Resume
- Data Analysis
- Statistical Software
- SQL
- Data Visualization
- Data Cleaning
- Machine Learning
- Excel
- Big Data
- A/B Testing
- Data Mining
- Critical Thinking
- Communication
- Problem-Solving
- Attention to Detail
- Teamwork
- Adaptability
- Time Management
- Curiosity
- Interpersonal Skills
- Analytical Mindset
Summary of Data Analytics Associate Knowledge and Qualifications on Resume
1. BS in Data Science with 2 years of Experience
- Relevant professional working experience
- Expert SAS programming and SQL querying skills
- Experience working with CMS data and/or VRDC
- Passion for making a difference in healthcare
- Solid understanding of Medical/Rx Claims, Clinical Data, and Eligibility
- Experience with clinical coding systems including ICD9/10 diagnosis codes, ICD9/10 procedure codes, CPT codes, revenue codes, provider NPI codes, NDC Rx codes
- Strong analytical problem-solving skills
- Ability to work independently and be a self-starter in a dynamic, fast-paced environment
- Strong written and verbal communication skills
- Must have a data-driven mindset with a passion for analysis
2. BS in Economics with 6 years of Experience
- Strong organizational skills, attention to detail, and ability to manage multiple projects with tight deadlines
- Superb analytical skills, persistence in problem-solving, and ability to learn quickly and independently
- Excellent written and oral communication skills
- Ability to correctly read and interpret financial statements such as 10K and 10Q, US GAAP, IFRS, and other regional accounting principles
- Experience working with AWS (Glue, Athena)
- Proficiency in SQL (SQL Server, PostgreSQL, MySQL)
- Experience with Data Catalog tools (Collibra)
- Proficiency in a statistical package (R), and a scripting language (Python)
- Proficiency in MS Office, especially MS Excel
- Exposure to third-party BI Tools including Tableau, Qlik, Looker, R Shiny
- Experience in data modeling and query optimization
3. BS in Computer Science with 5 years of Experience
- Relevant experience in data analytics roles within industry, academia, and/or relevant financial services.
- Experience working in data analytics/data science, statistical consulting/applied research roles, business intelligence, or data-focused risk analysis within the banking or financial services sector.
- Understanding/experience in applying data analytics in a business context and practical knowledge of relevant analytics software tools and infrastructure.
- Proficiency in SQL, preferably T-SQL, strong experience in reporting/dashboarding tools e.g. PowerBI, SSRS, Tableau
- Strong experience in R and/or Python and the relevant data manipulation and visualization libraries
- Knowledge of or willingness to acquire an understanding of the broader banking regulatory environment.
- Good analytical, problem solving and organizational skills as well as an ability to manage multiple requests and prioritize accordingly.
- Ability to critically assess complex/once-off issues and recommend/implement solutions.
- Experience or demonstrable interest in text analysis, network analysis, etc is desirable as well as a willingness to collaborate on innovative projects
- Strong verbal and written communication in particular the ability to relate to senior management and staff, with strong stakeholder focus.
- Must act professionally, ethically and with integrity.
4. BS in Information Technology with 7 years of Experience
- Experience in the UK Financial Services industry – ideally in Asset and Wealth Management
- Understanding relevant Financial Services regulation (e.g. ESG, MIFID, EMIR, AML, Dodd-Frank, FATCA, and Solvency)
- Understanding of the Business Value Chain
- Experience in building Artificial Intelligence and Machine learning models e.g. Natural Language Processing (NLP), Natural Language Generation (NLG), Deep Learning (Voice and Image recognition), Geospatial Prediction, Multi-layer Perceptron and other Neural Networks.
- Artificial Intelligence/Voice Technology experience e.g. IBM Watson, Amazon Echo, Google Home, Microsoft Cortana, Apple Siri.
- Experience in multiple tools/languages/frameworks within Big Data (Hadoop, Spark, Hive, MongoDB, Neo4j, HBase, Cassandra)
- Understanding of Artificial Intelligence and Cloud Platforms (e.g. Azure/IBM/Google)
- Advanced data analytics, building models in Python, R, SAS programming languages and libraries
- Experience in data analytics and visualization products such as D3, Power BI, Qlikview, Tableau
- Strong SQL and data manipulation skills
- Track record of managing data project delivery and project teams including the ability to meet deadlines, overcome challenges, manage stakeholder expectations and produce project deliverables
Editorial Process and Content Quality
This content is part of Lamwork's career intelligence platform and is developed using structured analysis of real-world job data, including publicly available job descriptions, skill requirements, and hiring patterns.
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