Sicredi

Analytics Culture and Data Science Management

Sicredi

full-time

Posted on:

Location Type: Hybrid

Location: Porto Alegre • Brazil

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Tech Stack

AWSAzureCloudDockerGoogle Cloud PlatformJavaPythonScalaSQL

About the role

  • Lead the organization’s central teams responsible for promoting and enabling the use of analytics and data science across the institution;
  • Propose improvements and lead the relationship between the Center teams and the business data teams, driving the evolution of the federated operating model;
  • Lead Sicredi’s Data & AI community, fostering engagement and the development of these disciplines to add business value;
  • Promote value generation for the business driven by analytics and data science, seeking to advance the maturity and autonomy of business data teams (spokes);
  • Act as a change agent and driver of data culture evolution by building relationships with peer areas, business units, product teams and vendors;
  • Provide and enable the use of innovative tools, analytical methods and data products aligned with business needs;
  • Lead the development of enabling components of the data science platform and promote their adoption and efficient use;
  • Participate in and represent analytics and data science topics for Sicredi at national and international events, seeking connections;

Requirements

  • Be a role model of excellence for your team;
  • Have excellent communication and presentation skills, as you will be a promoter and evangelist of the analytical culture;
  • Have experience managing leaders and technical teams;
  • Have an ambidextrous mindset, allowing space for challenging ideas and viewpoints;
  • Be resilient, flexible and agile;
  • Have strong ability and willingness to transit across different areas to exert influence, focusing on achieving common objectives in the federated model;
  • Have experience working with matrix teams (federated model);
  • Be skilled at time management;
  • Be passionate about learning and always open to new knowledge;
  • Have logical reasoning, analytical ability and creativity to find solutions;
  • Be proactive and creative;
  • Promote diversity;
  • Experience leading Data & AI teams;
  • Experience working in large enterprises within Data & AI teams;
  • Experience with ML/AI projects, from prototyping to model delivery;
  • Experience in developing Data & AI communities;
  • Experience in structuring corporate Data and Analytics teams;
  • Experience with DevOps tools (Docker, CI/CD);
  • Experience in time series data analysis, modeling, and machine learning libraries;
  • Experience with programming languages SQL, Python and/or R, Java and/or Scala;
  • Experience with orchestration frameworks and MLOps stack;
  • Experience with traditional Data Science techniques (clustering, A/B testing, etc.);
  • Experience working with cloud computing (AWS, Azure and/or GCP) and Databricks;
  • Experience with data analysis and visualization tools (Power BI, PowerApps, Report Builder);
  • Knowledge of data virtualization (Denodo) is desirable;
Benefits
  • Fixed 14th and 15th salary payments;
  • Profit sharing / Results participation (depending on seniority);
  • Health and dental plans with no co-payment;
  • Wellness programs via Wellhub (formerly Gympass): Nutrition, Psychology, Occupational Health, Massage, running group and local gym;
  • Meal and food vouchers – flexible allocation (%) between meal and food cards, with no co-payment;
  • Extended maternity and paternity leave;
  • Childcare or nanny assistance for children up to 6 years and 11 months;
  • Assistance for children with disabilities, no age limit;
  • Life insurance;
  • Private pension plan up to 7% of salary;
  • Training platform – Sicredi Aprende, with a wide range of courses;
  • 40-hour workweek – using a time bank system;
  • Remote work allowance (except for positions that require 100% on-site presence).
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
machine learningdata analysisdata sciencetime series data analysisprogramming languages (SQL, Python, R, Java, Scala)DevOps tools (Docker, CI/CD)MLOps stacktraditional Data Science techniques (clustering, A/B testing)data visualization tools (Power BI, PowerApps, Report Builder)data virtualization (Denodo)
Soft Skills
communication skillspresentation skillsleadershipresilienceflexibilityagilitytime managementcreativityproactivitypromoting diversity