Nejc Znidar available

Nejc Znidar

Data scientist, statistician

available
Profileimage by Nejc Znidar Data scientist, statistician from
  • Freelancer in
  • Graduation: Msc in Quantitative finance
  • Hourly-/Daily rates: 55 €/hour 400 €/day
  • Languages: German (Limited professional) | English (Full Professional) | Slovenian (Native or Bilingual)
  • Last update: 19.04.2018
KEYWORDS
PROFILE PICTURE
Profileimage by Nejc Znidar Data scientist, statistician from
SKILLS
Experience
  • Zalando SE. Tamara-Danz-Straße 1, 10243 Berlin, Germany.  Period: July 2016 - Februar 2018.
    • Making statistical and machine learning models (main models used: ARIMA, OLS, probit and logit, random forest, multilayer perceptron and some other models about time series analysis). Furthermore, preparing reports and forecast of different KPIs for different marketing channels which help optimizing the marketing expenditure budget (Working in marketing intelligence department).
  • SingularityNET. Period: September 2017-today.
    • Creating a stochastic financial model which quantifies risks for investors in SingularityNET. Model is based on past data of similar performances and current outlooks for the future.
  • Foreman assistant in Cestno gradbeno podjetje Novo mesto (CGP) (construction company). Period: June and July 2009 and July, August 2010.
    • Assistance at accounting, quotation creation, terrain work and others.
  • Actuarial practice at Triglav d.d. Mikloši?eva cesta 19, 1000 Ljubljana. Period: September 2013.
    • Basic actuarial tasks, examination of new program code, examination of online insurances and examining competitiveness.
  • Head of human resources AEGEE - non profit. Oct 2013 - Oct 2014.
    • Was in the board of Aegee Ljubljana 2013-2014. My role: Human resources. We organised several events in Ljubljana and other Slovenian towns and summer university in cooperation with Aegee Udine.

Knowledge
  • See detailed list of skills at http://nejcznidar.com/#services
  • Brief summary:
  •  Big data analysis.
  •  Statistical modeling.
  •  Machine learning – Gaussian mixture model, random forest (inlc. bagging), multilayer perceptron.
  •  Econometrics, regression;
  •  logit, probit model, linear regression, ordinary least squares, polynomial regression, GLM (generalized linear model), mixed probit and logit, fixed and random effects, nonlinear regression and others.
  •  Time series analysis and forecasting; ARIMA, MA (moving average) models, GARCH, TARCH, etc.
  •  Evaluating and interpreting statistical measures (deviation, kurtosis, mean, median, skewenes, percentiles, quantiles, etc.)
  •  Data retirement from Business objects, Microstrategy, SQL databases (including bigQuery), Google analytics, etc.
  •  Programming in R, Python (Anaconda) and Matlab.
  •  Excel, PowerPivot, PowerBI and Tableau.
  • Risk management and modeling.
  •  Financial modeling (stohastic modeling, option pricing, modeling interest rate, credit and exotic derivatives and other).
  •  Portfolio optimization, modeling term structure of interest rates.
PROJECT HISTORY
- Worked in Zalando 1 year 8 months. Worked on statistical data driven models to optimize marketing performance of a company. The goal was to optimize spending and get as many profitable customers as possible. Moreover, trying to quantify the exact effect of different marketing campaigns. Programming languages used: R, Python, SQL.

- SingularityNET: Built a stochastic model to predict possible future movements of cryptocurrency prices; used for risk management and decision steering. Programmed in Python.

- Causality detection: Determining causality in neuroscientific research; did EEG wave scans react to given signal? Programmed in R.

- Building fantasy basketball tool which forecasts most likely amount of statistics per player based on their past performance. Data was scraped from nba.com using APIs. Programmed in Python.

- Make a model to forecast future electricity prices based on past data. Time series analysis and forecast done in R.

- Writing a critical review of different statistical methods chosen in scientific paper (mainly what could be improved to make conclusions stronger).

- Writing a code to track cryptocurrencies in Matlab together with different crypto index choices. And then translating this code into R.

- Made a predictive model to predict companies' chance of going laying off people based on past layoffs, stock price movements, etc. to get an early automated signal. Done in R.

- Replicating a scientific study which calculates market premium using Ross recovery theorem (get's current state prices from real world option data). Done in Matlab.

- Made a script connecting BigQuery and Adwords to get some data engineering tasks done that. Using APIs and Python.

- Created predictive model to forecast future sales based on past data, seasonality and marketing efforts. Using Python.

- Simulating the burning forest given the wind directions, forest distribution, etc. Programmed in R.

- Creating R shiny application that determines the success of an add on SEA based on content written in description, headlines, path taken, etc.
TIME AND SPATIAL FLEXIBILITY
Flexible, though prefer working remotely.
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