Senior Data Scientist, Software Developer
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I have been working as a senior data scientist. My responsibilities are developing machine learning projects for the classification, prediction, clustering aims with various kinds of datasets on big data platforms such as Hadoop, i have also started to improve myself at computer vision subject.
Istanbul Technical University
Master of Science - MSc, Data Engineering - Big Data and Business Analytics
September 1, 2022 – August 1, 2023
Dokuz Eylul University
Bachelor's degree, Statistics
January 1, 2010 – January 1, 2013
Yıldız Teknik Üniversitesi
Associate's degree, Computer Technologies and Programming
January 1, 2007 – January 1, 2009
Nermin Bilimli Anadolu Teknik Lisesi
Yazılım
January 1, 2004 – January 1, 2007
Sabancı Üniversitesi
Senior Data Scientist
January 1, 2026 – May 1, 2026
Istanbul, Türkiye
Koç Holding A.Ş.
Koç Holding Chippin | Senior Data Scientist
July 1, 2022 – December 1, 2024
Istanbul, Türkiye
Burgan Bank
Credit Analytics Expert
May 1, 2021 – April 1, 2022
Istanbul, Türkiye
Türkiye İş Bankası
Obase Info. Technologies | Senior Data Scientist
December 1, 2019 – January 1, 2021
Istanbul, Türkiye
Etiya
Senior Data Scientist
August 1, 2019 – November 1, 2019
Etiya
Data scientist
March 1, 2014 – August 1, 2019
Etiya
R Software Developer
December 1, 2013 – February 1, 2014
Türkiye İstatistik Kurumu
Statistician intern
June 1, 2012 – July 1, 2012
Istanbul, Türkiye
Yedigen Bilgi Teknolojileri A.Ş.
Software Intern
June 1, 2009 – July 1, 2009
Istanbul, Türkiye
İstanbul Büyükşehir Belediyesi
Software Intern
June 1, 2008 – July 1, 2008
Istanbul, Türkiye
Mercedes-Benz Türk A.Ş.
Hardware Intern
June 1, 2007 – July 1, 2007
Istanbul, Türkiye
Mercedes-Benz Türk A.Ş.
Software Intern
July 1, 2006 – August 1, 2006
Istanbul, Istanbul, Türkiye
• Creation a version of stationary detection code for dagster orchestration
March 1, 2025 – April 1, 2025
Worked on stationary detection of vehicles and created a reviewed version to follow dagster project
• Creation of utilization code
March 1, 2025 – April 1, 2025
Working on the format for daily data with calculation of utilization and misuse columns regarding operational hours of vehicles
• Moving Detection for the vehicles
March 1, 2025 – March 1, 2025
Detecting moving period situation of the vehicles that come from telematic data related to automotive area
• Parser for Amazon S3 daily automotive parquet file
February 1, 2025 – March 1, 2025
Skills: Python
• Statistical changes around the refill events of vehicles
January 1, 2025 – February 1, 2025
Working on the fuel level statistical changes around refill events with using window approach
Cat Face Recognition
May 1, 2023 – May 1, 2023
İmage processing and face recognition methods were applied to a cat image to detect the parts such as 'eyes', 'nose' and 'face' by using cv2.
• Sales Amount forecasting with time series analyses
May 1, 2023 – August 1, 2024
To forecast next period (according months)consumer good sales amount of specific products,time series algorithmg were being used such as ETS,Holt Winter,ARIMA and LSTM and chosed the optimum with acceptable performance
Text Recognition with OCR
April 1, 2023 – May 1, 2023
Text Recognition for detecting the sensitivity of people by extracting the main subjects which were spoken in the tweets from different districts of Istanbul about the earthquake with applying a Computer Vision method called OCR (Optimal Character Recognition) on the images attached the tweets
• Sequential Pattern Mining for Netmera Web Search dataset Python 2023
January 1, 2023 – April 1, 2023
Constructing sequential patterns from the web search data based on sessions with an aim of exploring customer journey, by implementing spade algorithm on python.
• Chippin customer segmentation analysis using k-means based on the rfm values
December 1, 2022 – February 1, 2023
Skills: Python
• Working on the migrating codes from IBM Spss to Python
January 1, 2022 – April 1, 2022
Skills: Python · IBM SPSS
• Creating daily,weekly and monthly reports about the credit performances of the customers
May 1, 2021 – August 1, 2021
Skills: IBM SPSS
• Segmentation of customers in credit analytics system Python, IBM SPSS MODELER 2021
May 1, 2021 – January 1, 2022
: İndividual customer applications were clustered based on their demographic and banking behaviours as NPL ratios and DPD.
• Social_Network_Analysis_for_Detecting_Influencer_Vectors
January 1, 2021 – May 1, 2021
https://github.com/merwesarac/Social_Network_Analysis_for_Detecting_Influencer_Vectors
• Segmentation of digital banking customers IBM SPSS 2020
May 1, 2020 – September 1, 2020
Banking customers were clustered based on their digital banking behaviours as login counts,financial processes,non_financial processes,amounts and incomes.There were 2 approaches:Channel based micro value segments and the macro segments which includes ‘copper’,’bronze’,’silver’,’gold’ and ‘platinum’.The cluster means were used in cluster naming section.
• Learning GCP Machine Learning,Apache Nifi Tutorial
April 1, 2020 – June 1, 2020
Skills: GCP · Apache Nifi
Segmentation project codes were converted to Python in Microsoft Azure environment
February 1, 2020 – February 1, 2020
Skills: Python
Real time processing job created for the python outlier analysis with Kafka
February 1, 2019 – April 1, 2019
Kafka was used to write consumer and producer code for a simulated real time stream data
• Pattern mining marvel customer by machine learning
May 1, 2018 – June 1, 2018
For understanding the relationship between the transactions of a Digital platform customers,sequential pattern mining was implemented.And i constructed the relations between customer transcations by social network graphs.
• Prediction sale probability in future by markov chain technique
February 1, 2018 – March 1, 2018
Predict the possibility of a sale in future period by markov chain based classification in a time series perspective
• Forecasting project for ceramic products with using time series approaches
June 1, 2017 – November 1, 2017
Skills: R
• Predicting sales amount of a product of yearly data in daily format
April 1, 2017 – May 1, 2017
Predict sales amount of a product with grouping day of data,normalizate set and find best model like arima,ets,holtwinters,special regression,tbats and setar...for seasonal data and forecast the minimum value of standart error.
• Internal fraud link analysis
April 1, 2016 – May 1, 2016
I builded a system which can understand the relations between a few suspectful groups by social network analysis with R language
• Metrobus passenger counts for the next 5 minutes
November 1, 2015 – December 1, 2015
To understand the customer numbers for the next 5 minutes period in a station, I developed an optimization model and defined the conditions and target for the model
• Research user based collaborative filtering with recommender systems
September 1, 2015 – October 1, 2015
matching users' profile and behaviours with employers' ad in recommender systems caption and researching this knowledge
• Correlation and regression analysis about keywords
August 1, 2014 – September 1, 2014
discover correlation tween a gas station and the other factories' keywords' in social media so finding relations about sectors Rstudio,sqldf
• Sequential Pattern Mining Analysis against churn
June 1, 2014 – August 1, 2014
Sequential Pattern Analysis with unsupervised machine learning technique for determining churn of Digiturk platform customers
• Leader member detecter
May 1, 2014 – June 1, 2014
With social media users' tweets,followings,followers,retweeted,retweeting numbers and total user numbers ejected average tweet and follower.So the next step identified that effecting people crowds through degree centrality and combination of above informations.I profit from a facility of social network analysis in this work.Technolohy was sql,R,no sql.
• Determination of Twitter Users by their gender,age and job attributes
February 1, 2014 – May 1, 2014
In this project, we tried to determine Twitter Users in which class such as their gender,age and job attributes by examining posted comments (tweets) of people who registered in Turkish. There were 3 different aims as classify users based on their gender,age and job consequently.We developed many queries and criterias to determine Twitter Users' classes. We created models which could determine Twitter Users' different classes based on their gender,age and job. We took advantage of machine learning algorithms. In the classification process, we use many data mining algortihms such as Naive Bayes, Random Forest, Random Tree, j48, Support Vector Machine (svm), Sequential Minimal Optimization (smo).As a result of this project, we achived a high success in classification by using comments of Twitter Users.
• Apriori working
February 1, 2014 – March 1, 2014
constructing the apriori rules from keywords tribute an important person in social media with apriori in r
Karakalem Sergi Web Sitesi
February 1, 2013 – March 1, 2013
a web site includes chorcoal studies that have been coding with html5,html,Javascript,php and frameworks
Following the distribution of product parts to estimate the next values
November 1, 2010 – July 1, 2013
Following the distribution of product parts to estimate the next values, It was about my statistics bachelor thesis and we extracted the distributions of products about meeting the requirements of assumptions for the estimation model by Minitab.
Kütüphane Takip Programı
May 1, 2009 – August 1, 2009
C++ yazılımı ile kütüphane veri tabanında kayıt girme,arama,değiştirme,silme işlemlerini yapabilen program
Kütüphane Takip Programı
May 1, 2009 – August 1, 2009
Delphi ile yazdığım bir kütüphanenin kayıt,arama,değiştirme,istatistiklerini görüntüleme işlevlerini gerçekleştiren program.
Eczane Takip Programı
May 1, 2006 – June 1, 2006
Visual Basic ile kodladığım bir eczanenin reçete düzenleme,arama,değiştirme,silme işlemlerini yerine getiren program
Çanakkale Kişisel Web Sitesi
May 1, 2005 – August 1, 2005
Frontpage paket programı ile tasarımını bitirdiğim Çanakkale iline ait manilerin,kültürel bilgilerin,görsellerin bulunduğu web sitesi
OpenCV A-Z Uygulamalarla Görüntü İşleme
Udemy
June 25, 2026 – Present
Computer Technologies Certification
yedigen bilişim
June 25, 2026 – Present
R ile Veri Bilimi ve Machine Learning
Udemy
June 25, 2026 – Present
Cloud Storage Services on Microsoft Azure
Udemy
June 25, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse project portfolio spanning automotive, banking, e-commerce, and academic sectors, indicating adaptability to different business contexts. The projects involve various ML applications, suggesting a broad interest in the field. The experience in migrating codes and working with different platforms (IBM SPSS, Python, Azure, GCP) shows a willingness to learn and adapt to new technologies. The target role of ML Engineer aligns well with the candidate's extensive experience in data science and machine learning.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a focus on problem-solving and analytical thinking. Experience in creating policies for AI agents suggests an understanding of governance and ethical considerations in AI. However, without psychometric test results or interview data, it is difficult to assess soft skills like teamwork, communication, or stress handling.