Data Science Manager, Nextail

• Strong Mathematical Background: statistics, probability, operations research, simulations
• Understanding and modeling business problems by talking to customers and business experts with no math background
• Mathematical modeling and solving business problems
• Building the metrics and KPIs that will guide our progress
• Designing and making experiments to validate hypotheses
• Analyzing, understanding, and cleaning the data, extracting Insights
• Communicating complex things in a simple way. Talking the business language
• True interest and good skills in programming
• Good understanding of DS development processes and risks
• You are passionate about data science and a reference to your mates
• You are up to date with the methodologies and good practices for doing Data Science at scale
• Ability to deep dive and do research to find the state of art for applied math problems
• 2+ years of experience in a similar role, managing a data science team (4+ people) or multiple data science projects. Preferably in the product company
• More than 5 years experience working as a Data Scientist designing and building solutions for business problems
• Relevant experience building, delivering, and maintaining data science products from analysis to production both as an individual contributor and as a team lead
• Experience with the methodologies, practices, tools, and frameworks a data science team needs to achieve a good performance and scale-up
• Experience applying machine learning techniques to business problems
• Experience with time series forecasting
• Object-oriented programming with Python/Java
• Programming with python
• Working with Databases, SQL
• Experience building data pipelines
• Knowledge of version control tools like git

Desirable

• We’re seeking a Data Science Manager for our Data Science team. This new team member will play a crucial role in developing data science solutions from conception to implementation as we continue to enhance the world of retail and make it more sustainable
• The DS Team is part of the Product Team, our goal is to multiply the impact of our product on the business
• Data Science Techniques, AI, ML, Optimisation, Simulation, and Visualization, are the tools we always have at hand when we face a problem, but we will never use them in vain
• We work together with Product Managers, Developers, Data Engineers, and Business Experts to solve the end-to-end problem
• We are business-focused, we get into the skin of our customers, we learn to talk their language, and we feel their pain and their joy
• We believe in Data Ops, and Agile Data Science methodologies, in adding value fast, keeping things simple, and iterating to improve while the effort is worth it
• Life is short, our time is gold, we automate, we prioritize, we ensure focus, and we carefully choose our objectives to be sure to achieve them
• Our job is not finished when the model and the end-to-end solution are in production, or after the change management and operational details are closed, not even when we have strong evidence that the solution is solving the user problem and she is satisfied because after that we continue monitoring our models
• We are scientists and empiricists, we measure the impact on the business, and we progress with small steps, one at a time validating hypotheses at the lowest cost
• We are humble, we never know enough, we embrace uncertainty, and we are all the time learning from the wise and the data
• We listen carefully to the business experts, and our DS pairs and make sure we understand each other, we validate every assumption and hypothesis both with them and with the data, we are always thirsty for feedback and validation
• Discussion between pairs, working together, and challenging each other, are the fastest ways to solve a problem and to grow as a Data Scientist
• We have a culture of sharing, transparency, of meritocracy, of caring, and trusting each other