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  "basics": {
    "name": "Attila Barna",
    "email": "attila.barna@gmail.com",
    "summary": "Senior data analyst/scientist with experience across financial services, telco and igaming sectors. Proven ability to develop and implement advanced analytical tools, including propensity scoring, segmentation with predictive power and forecasting, as well as Monte Carlo simulations. Proficient in Python, SQL, and visual data mining tools such as SPSS Modeler and KNIME.",
    "location": "Budapest, Hungary"
  },
  "work": [
    {
      "company": "LVCD Entertainment (igaming)",
      "position": "Senior CRM Data Analyst",
      "location": "Budapest, HU",
      "endDate": "2026-09",
      "highlights": [
        "Developed a risk modelling tool for sportsbook bonuses with Monte Carlos simulation in Python including n% worst case scenarios.",
        "Created a turnover forecast tool for sportsbooks employing regression techniques in Python (85% of days within 10%).",
        "Developed a player value segmentation model (clustering and regression) which also create early VIP and churn signals.",
        "Played a leading role in sportsbook data being loaded into the data darehouse and the definition of numerous data mart tables"
      ]
    },
    {
      "company": "Intrum AB Hungary (credit management)",
      "position": "Senior Operations Data Analyst",
      "location": "Budapest, HU",
      "startDate": "2018-05",
      "endDate": "2023-11",
      "highlights": [
        "Analyzed collections efficiency to identify areas for improvement.",
        "Constructed a propensity-to-pay scoring model using logistic regressions in Python.",
        "Forecasted capacity requirements for operations leveraging Python scripts.",
        "Calculated conditions for debt settlement loan offers using R."
      ]
    },
    {
      "company": "Budapest Bank",
      "position": "Financial Data Lead Analyst",
      "location": "Budapest, HU",
      "startDate": "2016-03",
      "endDate": "2018-05",
      "highlights": [
        "Specified data warehouse developments from a Business Intelligence perspective.",
        "Validated a current account churn forecasting model built with decision trees in SPSS Modeler."
      ]
    },
    {
      "company": "UPC Hungary (cable and mobile telco provider)",
      "position": "CRM Data Mining Expert",
      "location": "Budapest, HU",
      "startDate": "2011-03",
      "endDate": "2016-03",
      "highlights": [
        "Automated and personalised CRM offers using SPSS Modeler.",
        "Provided end-to-end campaign support and conducted customer analytics."
      ]
    }
  ],
  "education": [
    {
      "institution": "Corvinus University of Budapest",
      "degree": "Economist",
      "field": "Actuarial science",
      "startDate": "2002-09",
      "endDate": "2007-06"
    }
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  "skills": [
    "SQL",
    "Python",
    "SPSS Modeler",
    "KNIME",
    "Jira",
    "Power BI"
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      "language": "English",
      "fluency": "Fluent"
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    "locations": [
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    "yearsOfExperience": 0,
    "seniority": "lead",
    "highestEducation": "Bachelor's"
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