Middle Data Analyst

🔥 7 hours ago

🇰🇿 Kazakhstan – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📉 Data Analyst

👻 Ghost score 16%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Intetics

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1995

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Intetics is an innovative company providing custom software development services, specializing in AI and machine learning solutions. They offer Remote In-Sourcing® to build expert teams for software engineering and data processing projects, along with advanced tools like TETRA™ for software quality assessment. Intetics aims to empower businesses by leveraging high-quality data and integrating modern technologies across various industries, including healthcare, finance, and more.

📋 Description

• Analyze large and complex datasets using statistical and quantitative methods. • Apply regression analysis, hypothesis testing, probability analysis, simulations, and time-series analysis to identify patterns and explain trends. • Validate analytical outputs, identify anomalies and outliers, and distinguish meaningful issues from normal variability. • Translate analytical findings into practical recommendations for customers and internal stakeholders. • Support business decisions with clear, evidence-based insights. • Design and develop dashboards, reports, and visualizations that make complex information easy to understand. • Adapt reporting formats and levels of detail for different audiences, from executive summaries to detailed analytical reports. • Monitor dashboards and reports to ensure their accuracy as data sources, business rules, and system configurations change. • Present analytical findings clearly to technical and non-technical stakeholders. • Research relevant datasets, industry benchmarks, and external context to support customer questions and internal decision-making. • Assess data quality and investigate inconsistencies or unexpected results. • Use AI tools to accelerate research, summarize findings, prepare documentation, and support analytical and quality-assurance workflows. • Stay informed about relevant analytical tools, data sources, methodologies, and industry best practices.

🎯 Requirements

• Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, or another quantitative field. • At least 3 years of professional experience in data analysis, business intelligence, or a related role. • Strong knowledge of statistics and quantitative analysis. • Advanced SQL skills and experience working with large datasets. • Strong proficiency with at least one data visualization platform, such as Power BI or Tableau. • Proficiency in Python, R, or another statistical programming language. • Experience creating dashboards, reports, and analytical presentations for different stakeholder groups. • Excellent written and verbal communication skills, with the ability to explain complex findings in clear, practical language. • Experience with cloud data platforms such as AWS, Microsoft Azure, or Google Cloud Platform. • Understanding of machine learning concepts and their practical applications. • Experience with A/B testing and experimental design. • Familiarity with data governance and data quality practices. • Experience using AI tools to improve research, analysis, documentation, or quality-assurance workflows. • Statistical analysis: regression, hypothesis testing, probability distributions, simulations, and time-series analysis. • Programming and querying: Python, R, SQL. • Python libraries: pandas, NumPy, scikit-learn. • Data visualization: Power BI, Tableau, matplotlib, ggplot2, or similar tools. • Data tools: advanced Excel, Jupyter Notebook, Git. • Databases: SQL Server, PostgreSQL, MySQL, or comparable relational databases.