Data Science Senior Specialist
Sofia - 9-11 Maria Louisa Boulevard
PwC
We are a community of solvers combining human ingenuity, experience and technology innovation to help organisations build trust and deliver sustained outcomes.Job Description & Summary
With offices across 155 countries and more than 327,000 people, we are among the leading professional services networks in the world. We help organizations and individuals create the value they are looking for, by delivering quality in assurance, tax, and advisory services. The Data Science team is positioned within the Risk Assurance Services (RAS) unit, which is an integral part of the overall Assurance practice. RAS undertakes a variety of complex information security consulting engagements, and business control reviews across a wide range of organizations.
We deliver actionable, data-driven insights to help our clients enhance operational processes and improve their understanding of customers. Examples of our solutions include pricing, product range and branch optimization, employee staffing and scheduling, customer segmentation, product recommenders, and customer lifetime value estimation. We combine unrivaled external and internal data sets to solve problems for clients across sectors, such as retail, financial services, and technology. Our team of data scientists and industry experts uses machine learning techniques and proprietary models to uncover results that can bring positive value to our clients.
The role:
As a data scientist at PwC, you will work with other data scientists, data engineers, machine learning engineers, designers, and project managers on interdisciplinary projects using statistics and machine learning to derive structure and knowledge from raw data across various industry sectors.
Duties and responsibilities:
Work in a multidisciplinary environment harnessing data to provide real-world impact for our clients based in the Southern and Eastern European (SEE) region, Central Europe, the UK, North America, and the Middle East
Influence many of the recommendations our clients need to positively change their businesses and enhance performance
Work on complex and extremely varied data sets from some of the world’s largest organizations to solve real-world problems
Develop internal tools for prototyping that might be used later to solve client problems. This includes application of object-oriented programming (OOP) principles
Write highly optimized code to advance our internal Data Science accelerators
Develop materials for assisting client pitches, engage in thought leadership activities, and contribute to the learning and development of colleagues
Have the opportunity to improve your technical skills, learn new technologies, and enhance your communication skills through various internal development programs
Skills & experience:
Graduate / postgraduate or Ph.D. degree in computer science, engineering, applied mathematics, statistics, quantitative social sciences or related fields
2 to 5 years of relevant experience providing advanced analytics in a financial services, retail, marketing, or other front office context
Programming experience in a number of the following technologies: Python, R and/or SQL
Good knowledge of statistical approaches including the following machine learning domains, such as:
1) Regression e.g. Linear Regression, Generalized Linear Model, Lasso, Ridge, Elastic Net
2) Classification e.g. Logistic Regression, Support Vector Machine (SVM), k-Nearest Neighbors (KNN)
3) Unsupervised ML e.g. Kernel Density Estimation (KDE), k-Means Clustering, DBSCAN, Gaussian Mixture Model (GMM)
4) Ensembles e.g. Random Forest, XGBoost, Light GBM, Stacking Regressor,, Isolation Forest
5) Deep Learning e.g. Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Long Short-Term Memory Network (LSTM)
Hands-on experience with some of the following popular data science Python libraries: Pandas, Numpy, SciPy, Scikit-Learn, Matplotlib, Plotly, Seaborn, Statsmodels, TensorFlow, Keras, PyTorch, Prophet, XGBoost, LightGBM
Exposure to big data processing tools, such as Azure, PySpark, DataBricks, etc. is a plus
Exposure to ML Ops, GitHub, Docker, is a plus
Good presentation and communication skills with the ability to explain complex analytical concepts to people from other fields
Fluency in English
What we offer:
Professional, positive, and team-oriented working environment
Professional experience in an international setting
Company training and excellent opportunities for professional and career growth
Challenging and interesting projects
Competitive remuneration and employee benefit programme including additional medical insurance, food vouchers, sports card, fringe benefit
Central office location
Opportunity to work from home
Only short-listed candidates will be contacted.
"PricewaterhouseCoopers Bulgaria EOOD, or PwC Legal Bulgaria Partnership, or PricewaterhouseCoopers Audit OOD, which runs a recruitment process, with its seat and registered address in 9-11 Maria Louisa Blvd., Sofia 1301, Bulgaria („PwC” or “we”) will be the controller of your personal data submitted in your application for a job. Your personal data will be processed for the purpose of performing a recruitment process for the job offered. If you give us explicit consent, your personal data will be also processed for participation in further recruitment processes conducted by PwC and sending notifications about job offers in PwC or job related events organized or with the participation of PwC such as career fair. Full information about processing your personal data is available in our Privacy statement."
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Azure Big Data Classification Clustering Computer Science Consulting Databricks Deep Learning Docker Engineering GitHub Keras LightGBM LSTM Machine Learning Mathematics Matplotlib NumPy OOP Pandas Plotly Privacy Prototyping PySpark Python PyTorch R RNN Scikit-learn SciPy Seaborn Security SQL Statistics statsmodels TensorFlow XGBoost
Perks/benefits: Career development Team events
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