Data Science Group Manager
hace 3 meses
The Data Science Group Manager is accountable for management of complex/critical/large professional disciplinary areas. Leads and directs a team of professionals. Requires a comprehensive understanding of multiple areas within a function and how they interact in order to achieve the objectives of the function. Applies in-depth understanding of the business impact of technical contributions. Strong commercial awareness is a necessity. Generally accountable for delivery of a full range of services to one or more businesses/ geographic regions. Excellent communication skills required in order to negotiate internally, often at a senior level. Some external communication may be necessary. Accountable for the end results of an area. Exercises control over resources, policy formulation and planning. Primarily affects a sub-function. Involved in short
- to medium-term planning of actions and resources for own area. Full management responsibility of a team or multiple teams, including management of people, budget and planning, to include performance evaluation, compensation, hiring, disciplinary actions and terminations and budget approval.
**Responsibilities**:
- Manages multiple teams or a functional area (depending on size of business) who support key functions within the business through collection, analysis, review, reporting, documentation and communication of business needs and requirements.
- Develops strategic direction for function.
- Accountable for budget, policy formulation and planning.
- Resolves complex and highly variable issues with substantial potential impact.
- Applies comprehensive understanding of BP&A concepts and procedures within own area and basic knowledge of other areas to resolve issues that have impact beyond own area.
- Directs subordinates' performance and makes recommendations for pay increases, hiring, terminations and other personnel actions.
- Manages compliance efforts to follow policies and procedures, as well as contribute to defining standards.
- Demonstrates an in-depth understanding of how own area integrates within the overall function to achieve objectives; requires a good understanding of the industry.
- Provides evaluative judgment based on analysis of factual information in complicated, unique and dynamic situations; draws on diverse range of internal and external sources; Accountable for end results.
- Utilizes excellent communication skills required in order to negotiate internally, often at senior levels (across functions); may communicate with external parties.
- Other duties and functions as assigned.
**Qualifications**:
- 10+ years experience with tools used for statistical analysis
- Experience with defining and implementing data science programs
- Knowledge of advanced statistical techniques and concepts and experience
**Education**:
- Bachelor’s/University degree or equivalent experience, potentially Masters degree
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
Are you looking to guide a delightful Data Science team? Do you enjoy innovating on behalf of customer? Do you love Data Science? CitiBanamex is looking for a strong leader for the Modeling Team.
S/he will be responsible for leading the modeling team that develops strategic data-driven solutions. He/She leads and directs a team of data scientists with different background such as Physics, Computer Science, Mathematics. He/She is focus on improving analytical capabilities across digital, retail products and customer experience
**Responsibilities**:
- Owner of the life cycle for each modeling project within Data and Analytics organization: Design, development, approval process, implementation, correct usage and maintenance of machine learning/AI tools across structured and unstructured data sets to identify underlying drivers of customer behaviors to improve sales, revenue, or any specific KPI depending on the use case.
- Drive innovative methods to improve current models that increase the revenue, sales or customer experience, maybe risk performance and accuracy of the models.
- Continues improvement of Machine Learning modeling training pipeline, considering different architectures and data building blocks
- Create deep level segmentations leveraging on enormous amounts of data from both traditional and alternative sources of information to improve the decision-making process in the bank.
- Decisive, yet open to learning: you will make many critical decisions every day with the certainty that you will be wrong some of the time.
- Develop and articulate analytical framework to solve business challenges.
- Extract actionable insights based on advanced analysis of customer behavior.
- Lead and develop reporting subordinates, especially around developing sound analytical approach to solve business problems.
- Drive innovative thinking about leveraging new tools/methods to transform the analytical capability
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