[WZA] Senior Applied Scientist

Company Description: Software Mind develops solutions that make an impact for companies around the globe. Tech giants & unicorns, transformative projects, emerging technologies and limitless opportunities – these are a few words that describe an average day for us. Building cross-functional engineering teams that take ownership and crave more means we’re always on the lookout for talented people who bring passion and creativity to every project. Our culture embraces openness, acts with respect, shows grit & guts and combines employment with enjoyment. Job Description: Project – the aim you’ll have The Client is Europe’s leading online platform for fashion, connecting customers, brands and partners across 17 markets. Position – how you’ll contribute Actively contribute to the team roadmap, and work closely with product managers and engineers to identify areas of opportunity and resource requirements to deliver impactful projects Conceptualize, prototype, and productionize state-of-the-art demand forecast solutions. You enjoy finding solutions to new complex problems and don’t mind getting your hands dirty (with pen and paper or in your IDE of choice). Communicate technical problems and results effectively with other team members and also with (less technical) stakeholders. Educate them about your products and solutions. Be the owner of the whole development cycle of algorithms - from opportunity discovery to production. Iteratively improve models and explore the art of possibility (e.g. new data sources, new ways of structuring the problem) Build model pipelines and streamline analysis processes, using common programming tools (e.g. Python, R, Scala, SQL, PyTorch, Tensorflow etc.) Qualifications: Expectations – the experience you need Master degree or above (PhD) in quantitative economics, statistics, mathematics, physics, operation research or a related quantitative discipline with a strong theoretical foundation in statistics, econometrics, time series analysis, and machine learning methodologies. Command of causal inference is a big plus At least 5 years of industry experience (3 years with PhD degree) in developing forecasting models, using both statistical methods and machine learning techniques. Understand the tradeoff of each method and their areas of applications. Have deep knowledge of the state of the art practices in forecasting, but also maintain a bias for simplicity Extensive experience with Python and its associated data science libraries, including writing production quality code (not just notebooks). Familiarity with optimization software such as Gurobi is a plus. Excellent verbal and written communication skills with a curious and self-starter mindset. Ability to unblock yourself, but also proactively request support when needed to remove roadblocks Additional Information: Our offer – professional development, personal growth Flexible employment and remote work International projects with leading global clients International business trips Non-corporate atmosphere Language classes Internal & external training Private healthcare and insurance Multisport card Well-being initiatives