Lead Data Scientist Resume Sample

Location

Poland

Rate

$30 / per hour

Years of experience

About

As a highly experienced data scientist with a strong academic background in bioinformatics and mathematics, I have honed my skills in building and deploying machine learning models across various domains, from gene regulation to programmatic advertising. My work at GynCentrum involved developing advanced CNN models to predict embryo viability, while at MediaMath/Varwise, I focused on deploying machine learning models for the programmatic advertising domain using tools like DataBricks, AWS, and PySpark. I have also led teams in the development of financial models at the Warsaw Stock Exchange, where I contributed to the accurate prediction of financial trends using cutting-edge techniques like RNNs and Transformer architectures. In addition to my hands-on experience in data science and machine learning, I have a strong foundation in software development and statistical modeling. My role as a Scientific Software Developer at DNA Electronics involved developing sequence calling algorithms and clustering large datasets. At ST-YL.com, I built a visually-aware recommender system and deep neural networks for image classification. My technical skills span a wide range of programming languages and tools, including Python, SQL, Spark, and AWS, making me proficient in handling complex data engineering tasks and deploying production-ready machine learning solutions.

Tech Stack

Data Science, AWS, Bash, C, C#, C++, Docker, Git, Linux, Machine Learning, MATLAB, Matplotlib, Numpy, Pandas, PySpark, Python, R, Tensorflow

Experience

At GynCentrum, developed advanced CNN models to evaluate embryo viability from video data, using frameworks like PyTorch, Detectron2, LSTM-CNN, and 3D-CNN models.
At MediaMath/Varwise, developed and deployed machine learning models for the programmatic advertising domain, leveraging tools like DataBricks, AWS, PySpark, and Facebook Prophet.
At Warsaw Stock Exchange, managed a team of data scientists while contributing to the development of financial models using PySpark, Dask, and Kafka.
At ST-YL.com, built a novel visually-aware recommender system based on Bayesian statistics, and developed deep neural networks for image classification.
At DNA Electronics, developed sequence calling algorithms using scientific Python and employed clustering algorithms for processing large datasets.
Designed and implemented sales forecasting systems using machine learning models trained on time series data, contributing to accurate financial predictions.
During PhD at the University of Manchester, built machine learning models of gene regulation from ChIP-seq and RNA-seq data, utilizing high-performance computing clusters.

Employment history

Lead Data Scientist, GynCentrum May 2022 - Present

Developed cutting-edge CNN models to evaluate the viability of embryos from video data.
Employed advanced frameworks such as PyTorch, Detectron2, LSTM-CNN, and 3D-CNN models.
Utilized GitLab CI/CD for deployment of models and processes.
Collaborated with cross-functional teams to integrate models into production environments.

Data Scientist, MediaMath/Varwise September 2022 - June 2023

Developed and deployed machine learning models in the programmatic advertising domain.
Leveraged tools like DataBricks, AWS, PySpark, and Facebook Prophet for model development.
Collaborated with software developers to ensure seamless integration and production-ready code.
Presented results and model insights to senior stakeholders and clients.

Expert Data Scientist, Warsaw Stock Exchange January 2020 - May 2022

Managed a team of data scientists while actively contributing to coding efforts.
Developed financial models using PySpark, Dask, Kafka, and incorporated some JavaScript.
Accurately predicted financial trends using RNN, LSTM, Transformer architecture, and Gaussian Process.
Collaborated closely with business stakeholders to align data solutions with organizational goals.

Scientific Software Developer, DNA Electronics August 2019 - March 2020

Developed sequence calling algorithms using scientific Python (Numpy, Pandas, Numba).
Utilized Batch K-means and DBSCAN clustering algorithms for processing large time course data.
Applied OpenCV for image segmentation tasks in biological data analysis.
Prepared data visualizations using Matplotlib for reporting and analysis.

Senior/Lead Data Scientist, ST-YL.com July 2018 - July 2019

Built a novel visually-aware recommender system based on Bayesian statistics.
Developed deep neural networks for classification and search of visually similar items.
Administered Linux-based dual-GPU server and remote cloud/production server on AWS.
Converted business needs into machine learning solutions and delivered production-ready products.

Data Scientist, ING BANK February 2018 - July 2018

Developed novel attribution models for marketing based on Markov chains and their stationary distributions.
Utilized SQL (HIVE), Spark (PySpark), and Hadoop for distributed processing and data storage.
Analyzed customer data to optimize marketing strategies and improve campaign effectiveness.
Collaborated with marketing teams to implement data-driven decision-making processes.

Machine Learning Engineer, Amplyfi LTD March 2017 - September 2017

Applied Random Forest and Logistic Regression to filter out irrelevant data in large text documents.
Performed hypothesis testing on bigrams using likelihood ratio tests with data from Wikipedia.
Conducted topic modeling and meaning extraction from large volumes of text documents.
Extensively used Python libraries such as Numpy, Pandas, NetworkX, and Scikit-learn.

Education history

University of Manchester 2012 - 2017 PhD Bioinformatics

Manchester Metropolitan University 2008 - 2011 BSc Mathematics

Manchester Metropolitan University 2007 - 2008 Chemistry

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