Top Data Analyst Jobs in Turkey

Analyze large-scale data to generate insights for product, marketing, and business strategy. Build and maintain dashboards and reports using analytics tools, perform ad-hoc analyses, communicate findings clearly, and collaborate cross-functionally to define data requirements and support fast decision-making.

Analyze large-scale on-chain data to detect anomalous transactions, develop detection mechanisms and risk monitoring frameworks, apply supervised and unsupervised ML, identify malicious accounts via community-discovery algorithms, and design integrated on-chain/off-chain prevention and control systems.

Analyze large datasets to identify trends and deliver actionable insights; design and monitor KPIs; build and maintain dashboards and reporting frameworks; conduct ad hoc analyses; ensure data quality and support reporting infrastructure in partnership with product and business teams.

Early-career Data Analyst responsible for designing and owning core metrics and dashboards, analyzing transaction/customer/credit data to inform credit, fraud, AML, portfolio and growth decisions, building data pipelines and automations with SQL and Python, partnering with cross-functional teams, and owning compliance reporting. Emphasis on turning ambiguous problems into reliable analytical systems and applying GenAI/LLMs for practical automation.

Analyze and instrument offsite discovery and SEO/GEO performance for ecommerce sites. Build integrations, ETL pipelines, and models to track organic and AI-driven traffic. Create tooling and frameworks for technical site audits, landing page modelling, SEO experiments, and enablement for product and customer teams.

Drive end-to-end product analytics for user growth and product strategy: define metrics, design and analyze A/B tests, handle PB-scale behavioral and transactional data, build dashboards, predictive models, and deliver actionable insights to product and business stakeholders.

Support multilingual data quality by analyzing and cleaning text data, developing parsers, evaluating text classifiers, translating taxonomies (Skills, Titles, Occupations), and partnering with Linguistics and Engineering to deliver high-quality global data.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

Support development and maintenance of SQL-based data pipelines and analytics workflows. Assist data standardization, build and optimize data models, dashboards, and reports. Perform ad-hoc analyses, monitor data quality, implement validation logic, and collaborate on cross-functional data and risk projects under mentorship.

Entry-level Product Data Analyst internship supporting product analytics: build and analyze conversion funnels, evaluate A/B tests, create dashboards, respond to ad-hoc data requests, write SQL pipelines, monitor data quality, and translate findings into visual summaries to inform product decisions.

Analyze and cleanse raw data, build and maintain data pipeline architecture, and generate actionable business insights. Promote a data-driven culture, plan and execute BI projects, and apply predictive modeling, machine-learning, clustering and classification techniques. Create dashboards and reports (Tableau, Looker) to improve product and customer analytics and business processes.

Build and maintain dashboards, analyze large datasets to surface actionable insights, ensure data accuracy and integrity, and develop scalable analytics deliverables to support product and marketing decisions.

Analyze mobile games data to track performance, design and execute A/B tests, report on user engagement, and recommend optimizations.

Analyze player behavior to produce actionable insights, build Python tools and algorithms for procedural level generation, automate testing/validation of generated levels, write SQL queries to extract data, and create clear visual reports for technical and non-technical stakeholders to guide product decisions for mobile games.

Partner with Marketing, Sales, Finance, Product and other teams to turn business questions into actionable analysis. Own end-to-end analytics: build datasets and dashboards (dbt, LookML), maintain metric definitions and caveats, use and curate agent tooling for trustworthy answers, and contribute small data platform and pipeline improvements.

Analyze billing and support performance, build and maintain data pipelines, apply statistical forecasting and A/B testing, collaborate cross-functionally, document analyses, and provide recommendations to reduce financial risk, disputes, churn, and operational inefficiencies.

The Data & Monetization Analyst will design A/B tests, analyze KPIs, develop player segmentation tools, and support multiple teams with data insights.

Analyze large-scale user and product data, design and evaluate A/B tests, define and validate product and business metrics, build dashboards and reports, and partner with engineers, data scientists, product, and customers to translate insights into product improvements.

The Lead Data Analyst will mentor the data team, analyze player behavior and game metrics, create dashboards, and enhance data quality for strategic decisions.

Lead consolidation, validation and integrated reporting of project performance data across engineering, procurement, fabrication and project controls. Develop executive dashboards and advanced analytics (including Monte Carlo simulation and contingency analysis), support governance, and partner with multidisciplinary project teams on major EPC, LNG and energy infrastructure projects.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

Validate and reconcile fund and financial data, investigate and resolve data issues, own daily operational workflows, partner with data and engineering to improve quality, and build/document scalable procedures to support private-markets operations.