Senior Data Scientist

Role Overview

• Selecting appropriate analytical techniques and algorithms to solve business challenges.
• Ability to choose the right tools and the right infrastructure for data science projects and articulate those decisions.
• Ensuring quality delivery according to the standards and best practices methodology.
• Technical mentorship to junior team members.
• Formulating and leading data science projects.
• Driving the development of the SW code (quality, documented, and reusable) to execute data science algorithms.
• Communication & collaboration with diverse stakeholders.
• Understanding of the business context of the decisions to be supported.
• Building mathematical, statistical, and machine learning models using available data.
• Use of R and/or Python to design and develop analytical models and data science products using advanced techniques such as simulations, optimizations, and machine learning.
• Assessment of the output of analytical solution and use the data to draw conclusions, identification of options, and making recommendations.
• Interpret the results and provide the advices to the business stakeholders.
• Building and maintaining knowledge on the data sources, the data quality, and metadata.
• Recognition of the repeatable situation and suggesting the appropriate level of automation of analytics.
• Promotion of a culture of modelling and analytics as a differentiator and competitive advantage – an environment that places high value on embedding analytical tools within business processes, and using information to make fact-based decisions.
• Staying in touch with modern methodology within predictive modelling.

Requirements

• MSc or PhD in Mathematics, Statistics, Econometrics, Machine Learning, Computer Science, Physics, or other related field.
• Passion for advanced analytics and mathematics.
• Passion for good quality code.
• Record of delivering successful data science products is an advantage.
• Experience with building predictive ML pipelines.
• Experience with simulations, synthetic data, and building digital twins would be a big advantage.
• Strong communication and interpersonal skills, including the ability to make high-level presentations to senior executives.
• Ability to analyze business challenges and define data science projects.
• Ability to formulate models, program them and run in an appropriate system.
• Extensive knowledge in one or more of the following areas: statistical analysis and modelling, probability, stochastic processes, econometrics, machine learning, optimization, simulations, and software development.
• Strong analytical and problem-solving skills and ability to work with incomplete or imperfect data, including the ability to interpret and use the analytics results within the real business context.
• Experience with version control systems such as git and collaboration tools.
• Experience and/or ability to quickly learn new tools like Databricks, HPC.
• Ability to work both independently and collaboratively within a global team.

Tech Stack

• Python

Benefits

• Exciting work in a great team, global projects, international environment.
• Opportunity to learn and grow professionally within the company globally.
• Hybrid working model, flexible role pattern (e.g., even 80% full-time is possible in justified cases).
• Pension and health insurance contributions.
• Internal reward system plus referral programme.
• 5 weeks annual leave, 5 sick days, 15 days of certified sick leave paid above statutory requirements annually, 40 paid hours annually for volunteering activities, 12 weeks of parental contribution.
• Cafeteria for tax free benefits according to your choice (meal vouchers, sport, culture, health, travel, etc.), Multisport Card.
• Vodafone, Raiffeisen Bank and Foodora discount programmes.
• Up-to-date laptop and iPhone.
• Parking in the garage, showers, refreshments, massage chairs, library, music corner.
• Competitive salary, incentive pay, and many more.