Overview:
*data scientist | level: staff iv*
recruiter: manuel garcia
this position reports to: daniel perez, manager i, business analytics
this position will be responsible for the creation and optimization of the reports / dashboards to support the decision-making process across the americas.likewise, it will support with ad-hoc analysis with valuable information for greater visibility towards the management team.will report directly to the supervisor gbs - business analytics team in guadalajara
job qualifications:
qualifications:
- bachelor's degree in finance, business intelligence, finance engineering
- experience in data analysis, reports, and dashboards creation
- experience in business intelligence tools (microstrategy)
- experience experience in machine learning
- desirbale experience in python
- proficient in excel
- time management
- presentation, reporting and communication skills
40% technical
- statistics & mathematics 25%
- software engineering 25%
- programming 25%
- data wrangling 15%
- machine learning 10%
40% analytical
- sales & marketing plan 30%
- business acumen 30%
- analysis 25%
- data visualization 10%
- intellectual curiosity 5%
20% interpersonal
- teamwork 25%
- communication 20%
- data intuition 20%
- english 15%
- project management 10%
- leadership 10%
this position should have an internal sublevel, according to the next qualifications ( appendix ):
- entry: between 1.6 and 2.0
- plain: between 2.1 and 2.5
- senior: between 2.6 and 3.0
detailed responsibilities:
- performing complex analytics and statistical modelling on large data sets to identify market/business sector trends, customer buying patterns, etc. to inform business, product development, and marketing decisions.
- creating data mining architectures/models/protocols, statistical reporting, and data analysis methodologies to identify target customer segments and simulate the impact of new product launches and marketing campaigns, etc.
- quantifying the revenue impact of various online marketing, e-commerce strategies, promotions, etc.
- analyzing business intelligence data to inform business and product decisions
- blending historical data from available industry reports, public information, field reports or purchased sources as input to analyses
- identifying and analyzing industry/geographic trends and competitor market strategies and monitoring current/potential customer trends.
- partners with other areas of the business (e.g., marketing, logistics, customer service, etc.) to model the outcome of implementing potential business strategies.