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Intuit Senior Data Scientist Kenya, Nairobi County, Nairobi 100170854
27.03.2025
Responsibilities
- Work cross-functionally with our Partners, Quality Management, and service delivery teams to understand key business challenges and objectives and build tech driven models and insights to address them
- Leads the full cycle of iterative experimentation, big data exploration, including hypothesis formulation, algorithm development, data cleansing, testing, insight generation/visualization, and action planning
- Uses considerable expertise and independent judgment in collaborating with peers, data engineers, and business analysts in designing and implementing the research strategy needed to methodically and iteratively structure, extract, cleanse, sample, test, validate, and communicate data-driven insights from complex sources and significant volumes of data for complex and unique business problems
- Applies proven methods and hacking skills in working with divergent data types, data scales, and big data (petabytes), to explore and extrapolate data-driven insights using advanced, predictive statistical modeling and testing applied to data acquired and cleansed from a range of sources (relational and non-relational NoSQL databases)
- Provides to business stakeholders the entrepreneurial guidance essential for appropriately interpreting and building on findings, and fully exploiting the insights revealed through the research
- Develop and implement natural language processing (NLP) models using large language models (LLMs) like GPT-3 to analyze call center conversation transcripts and identify key themes, topics, and sentiment
- Clearly communicate analytical insights and model results to key stakeholders through reports, presentations, and visualization tools.
- Develop interactive dashboards and visualizations to track service quality KPIs and insights over time
Qualifications
- Prior experience working in a call center environment . Knowledge of call center technologies - things like phone systems, CRM software, call recording systems, etc.
- 6+ years experience building ML models utilizing audio, speech, and video data - strong signal processing, ML/DL and NLP foundations are needed along with hands-on expertise using Python audio/speech libraries (Speech Recognition, Librosa, PyDub, PyTorch etc.)
- Experience with machine learning and deep learning models for speech and NLP tasks. Knowledge of techniques like Recurrent Neural Networks, Transformers etc.
- Ability to manipulate and process large, complex multimedia datasets
- Strong communication and presentation skills to executive audiences
- MS or PhD in Computer Science, Statistics, Math or related field preferred
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