Sicredi

Analytics Culture and Data Science Management

Sicredi

full-time

Posted on:

Location Type: Hybrid

Location: Porto Alegre • Brazil

Visit company website

Explore more

✨ AI Apply
Apply

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
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