Data Manager managing data analytics consulting projects at PwC. Collaborating on data - driven solutions and overseeing implementation while maintaining client relationships.
About the role
- Entry-level data analyst supporting AI team in developing and evaluating AI products. Responsibilities include data exploration, performance monitoring, and cross-functional collaboration.
Responsibilities
- Data Exploration & Visualization: Investigating data to identify trends, anomalies, or patterns using tools like SQL, Tableau, Power BI, or Python libraries like Matplotlib or Pandas.
- Performance Monitoring: Analyzing the performance metrics of AI models such as accuracy, precision, recall, F1 score, etc., and identifying areas for improvement.
- Performance Hardening: Provide quantitative and qualitative insights for feature improvement, contributions in model development process through data or design.
- A/B Testing & Experimentation: Conducting experiments to test the efficacy of AI models or changes to AI systems, using A/B testing or other experimental designs.
- Root-Cause Problem Solving: Carry out failure investigation of AI events including but not limited to recalling and reviewing events where AI algorithms fail in the field and then compare to backtest (test infra) results in consultation with model development team and jointly layout directions for feature improvements.
- Reporting: Creating dashboards and reports to communicate the results of data analyses to business stakeholders.
- Cross-functional Collaboration: Participate in cross team coordination with the Data Annotation, QA, and Product teams.
Requirements
- Bachelor’s Degree in Computer Science, Electrical Engineering, or related field
- Experience in SQL & Redash / Snowflake, writing complex queries
- Experience in Python and data analysis & visualization tools (pandas | plotly | seaborn)
- Strong problem-solving & communication skills
- Demonstrated experience in Computer Vision or Machine Learning is a strong plus (FYP, Coursework, Freelance or side project or industrial experience)
Benefits
- Creating a diverse and inclusive workplace
- Equal opportunity employer
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Principal Data Science Engineer at Qodea leading development of AI - driven reasoning tools and recommendation systems. Collaborating to bridge advanced analytics with practical implementation in Buenos Aires.
Lead Data Scientist at Target developing predictive and prescriptive algorithms for supply chain optimization. Collaborating across teams to foster data - driven decision - making while ensuring continuous innovation.
Data Scientist working with data analytics to drive efficiency improvements in the energy sector. Collaborate with teams to build and deploy models for actionable insights.
Senior Data Scientist at Betclic developing data products and user experiences in an innovative gaming environment. Collaborating across teams to drive data - driven decisions and product improvements.
Senior Data Science Engineer developing and maintaining machine learning models for fintech company. Collaborating with cross - functional teams to drive product improvements and user insights.
Senior Data Scientist in a Legal AI company focusing on ML operations analytics, collaborating with teams for effective legal outcomes.
Senior Manager of Data Analytics leading high - impact analytics projects for business strategy at Conduent. Overseeing teams to develop data models and present insights to leadership.
Team Lead for Data Science at PAIR Finance focusing on machine learning product development. Leading a team to innovate in debt collection with AI - driven insights.
High - impact Data Scientist driving complex data projects leveraging AI tools at dLocal, influencing strategic decisions in payments sector.