Lead Data Scientist en Sant Cugat del Vallès

Applies advanced subject matter knowledge to solve complex business issues and is regarded as a subject matter expert. Frequently contributes to the development of new ideas and methods. Works on complex problems where analysis of situations or data requires an in-depth evaluation of multiple factors. Leads and/or provides expertise to functional project teams and may participate in cross-functional initiatives. Acts as an expert providing direction and guidance to process improvements and establishing policies. Frequently represents the organization to external customers/clients. Exercises significant independent judgment within broadly defined policies and practices to determine best method for accomplishing work and achieving objectives. May provide mentoring and guidance to lower level employees.

Responsibilities:

• Leads complex data and business analyses to develop business plans, and identifies recommendations and insights.
• Works independently to construct highly complex statistical and financial models to forecast business performance; coaches others on model development.
• Establishes the metrics required to measure business performance, and develops the process for identifying and addressing performance gaps.
• Manages complex, time- sensitive market research projects and prepares synthesized intelligence reports with clear implications.
• Leads cross-functional teams across the entire span of business planning activities.
• Contributes to priority projects by adding creative insights and developing recommendations.
• Partners with business leaders to develop business plans and proactively identify new opportunities.
• Develops go-forward business plan recommendations based on potential risks and returns.
• Identifies cutting-edge analytical tools, models, and methods for making key business decisions.

Education and Experience Required:
Typically 6-10 years work experience in strategy, planning, operations, finance, or related functional area. Advanced university degree (e.g., MBA) or demonstrable equivalent.

Knowledge and Skills:

• Extensive knowledge of research methodology for key business issues.
• Excellent analytical thinking, technical analysis, and data manipulation skills.
• Ability to leverage new analytical techniques to develop creative approaches to business analysis.
• Extensive knowledge and understanding of how to analyse business problems using Excel, Access, statistical analysis, and financial modelling.
• Strong business acumen and technical knowledge within area of responsibility.
• Excellent verbal and written communication skills.
• Very strong project management skills, including leading large, cross-functional initiatives.
• Strong relationship management skills, including partnering and consulting.
• Developed leadership skills, including team-building, conflict resolution, and management.
• Ability to identify emerging trends from market and industry data.
• Ability to apply advanced statistical methodologies such as mixed model (random and fixed effects), simultaneous equations, time series based methods (ARIMA, Causal Autoregressive Mixed Models), neural networks, and multinomial discrete choice. Experience developing and implementing machine learning techniques in real time (e.g. API, PMML, Java, C, RPMML).
• Advanced hands on experience in Statistical Software (e.g. SAS, R, Python) and big data environments (e.g. cloud (e.g. AWS, Azure), and on-prem (e.g. Hadoop). 
• Ability to comprehend and apply principles of advanced calculus, machine learning and advanced other statistical theory. 
• Work effectively in cross-functional teams, having demonstrated strong partnerships with both internal and external business partners and alliances.
• Demonstrated ability to collect and organize data, work effectively with complex relational databases, conduct analysis and report on and apply results to “actionable insights/recommendations.”
• Solid data modelling experience is required with proven application in applying Decision Trees, Regression analysis, Neural Network and other data mining techniques, experience with time series and experimental design.