IT ANALYST

Job Title: IT Analyst
Job Type: (Remote)
Job Summary
The IT Analyst — Data Analytics & Data Science is responsible for analyzing complex business and technology data to provide actionable insights, support data-driven decision-making, and improve IT and business performance. This position works with business stakeholders, data scientists, data engineers, IT teams, and management to collect, prepare, analyze, visualize, and interpret data.
The role supports data analytics, predictive analysis, reporting, data quality, and technology initiatives while helping the organization identify trends, improve processes, manage risks, and make informed business decisions.
Key Responsibilities

Collect, integrate, clean, and analyze data from multiple business and IT systems.

Perform exploratory data analysis to identify trends, patterns, relationships, and anomalies.

Develop reports, dashboards, and data visualizations using tools such as Power BI, Tableau, or similar platforms.

Write SQL queries to extract, transform, validate, and analyze data from relational databases.

Support data science and advanced analytics initiatives through data preparation and analysis.

Develop statistical analyses, forecasts, and predictive models under established methodologies.

Assist data scientists with data preparation, feature engineering, model testing, and model evaluation.

Analyze IT performance, application usage, system availability, incidents, service requests, and operational metrics.

Develop and monitor key performance indicators (KPIs) for IT and business operations.

Identify trends and patterns that may indicate system performance issues, operational risks, or opportunities for improvement.

Conduct root-cause analysis using quantitative and qualitative data.

Validate data accuracy, completeness, consistency, and reliability.

Investigate data quality issues and work with IT and business teams to resolve discrepancies.

Develop automated reporting and analytical processes to improve efficiency and reduce manual work.

Support data integration, data migration, and data transformation activities.

Collaborate with data engineers to improve data pipelines, datasets, and data availability.

Document data sources, business rules, calculations, analytical methodologies, and reporting processes.

Translate business and IT questions into analytical requirements and measurable outcomes.

Present analytical findings and recommendations to technical and non-technical stakeholders.

Support data-driven technology decisions and IT improvement initiatives.

Assist with experimentation, A/B testing, statistical analysis, and scenario analysis when applicable.

Monitor analytical models and reports to ensure continued accuracy and reliability.

Support data governance, privacy, security, and data management practices.

Stay current with data analytics, artificial intelligence, machine learning, and emerging technology trends.

Qualifications

Bachelor's degree in Data Science, Data Analytics, Computer Science, Information Technology, Statistics, Mathematics, Business Analytics, or a related field.

2–5 years of experience in data analytics, IT analysis, business intelligence, or a related field.

Strong SQL skills and experience working with relational databases.

Proficiency in Excel and experience with data analysis and visualization.

Experience with Power BI, Tableau, or another business intelligence platform.

Working knowledge of Python or R for data analysis.

Strong understanding of data analysis, statistics, and data visualization principles.

Experience with data cleaning, transformation, validation, and quality analysis.

Strong analytical and problem-solving skills.

Excellent written and verbal communication skills.

Ability to communicate technical data findings to non-technical stakeholders.

Preferred Qualifications

Master's degree in Data Science, Statistics, Computer Science, Analytics, or a related field.

Experience with machine learning and predictive analytics.

Knowledge of statistical methods such as regression, classification, clustering, and time-series analysis.

Experience with cloud data platforms such as AWS, Microsoft Azure, or Google Cloud.

Experience with data warehouses, data lakes, and ETL/ELT processes.

Familiarity with Databricks, Snowflake, BigQuery, or similar data platforms.

Experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch.

Knowledge of APIs and data integration technologies.

Experience with IT service management data and tools such as ServiceNow.

Knowledge of data governance, data security, and privacy practices.

Key Skills

Data Analytics

Data Science

SQL

Python / R

Statistical Analysis

Predictive Analytics

Machine Learning

Data Visualization

Power BI / Tableau

Data Cleaning & Transformation

Data Quality & Validation

Exploratory Data Analysis

Forecasting

KPI Development

Root-Cause Analysis

Data Modeling

ETL / ELT

Data Integration

Business Intelligence

IT Performance Analytics

Core Competencies

Data Analysis: Ability to transform raw data into meaningful insights and actionable recommendations.

Technical Expertise: Ability to work with databases, analytical tools, programming languages, and data platforms.

Statistical Thinking: Ability to apply appropriate statistical methods to analyze trends, relationships, and business problems.

Problem Solving: Ability to investigate complex data and IT problems and identify practical solutions.

Data Quality: Ability to validate data and identify inconsistencies that could affect analytical results.

Communication: Ability to explain analytical findings and technical concepts clearly to business and IT stakeholders.

Business Understanding: Ability to connect data insights to business objectives, operational performance, and IT strategy.

Collaboration: Ability to work effectively with data scientists, engineers, IT professionals, business analysts, and business leaders.

Originally posted on Himalayas