Data Science Manager

Job Description & Summary

With offices across 149 countries and more than 370,000 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.

About the team:
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 science manager 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 with data from diverse structured and unstructured data sources in both batch and streaming modes 
• Consult clients or internal teams to prepare complex data analyses and models that help solve client problems and deliver significant measurable impact 
• Manage the entire analytical process – from outlining the type of solution through implementation, interpretation of results and transferring capabilities to the client or colleagues
• Constructively discuss your findings in collaboration with consultants and clients while always looking for the best solution. Working on projects and exchanging experiences with your colleagues means you will face new intellectual challenges on a daily basis while continuously building your methodological knowledge and skills
• Develop internal accelerators for prototyping that may be used later to solve client problems
• Work closely with the Data Science Team Lead on business development opportunities and support demos for prospective clients 
• Mentor, coach, and review the work of junior data scientists 
• Have the opportunity to improve your technical skills, learn new technologies, and polish your communication skills through various company development programs 

Skills & experience:

• Degree in mathematics, statistics, computer science, engineering, physics, or related fields
• 5+ years of programming experience with languages such as Python, R, and SQL (candidates with less experience will be considered for a more junior position)
• Proven application of advanced analytical, data science and statistical methods in industries like financial services, retail, and technology
• Professional experience in cloud-based analytics tools from market-leading platforms such as MS Azure, GCP and AWS
• Hands-on experience in the following machine learning domains: 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),  Generative Adversarial Network (GAN)
• Exposure to ML Ops, GitHub, Docker, is a plus
• Practical experience in Generative AI application development, is a plus
• Excellent problem-solving and quantitative skills, including the ability to disaggregate issues, identify root causes, and recommend solutions
• Proven leadership with the ability to inspire others, build strong relationships, and create true followership, result-driven achievers
• Strong people skills, team-orientation, and a professional attitude
• 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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