Quantitative Researcher
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Job Description
About Avanade
Avanade is Microsoft’s Global Alliance Partner of the Year (14 years in a row), offering exceptional development and training opportunities. The company fosters a diverse and inclusive culture where employees can thrive, innovate, and create solutions that improve the way humans work, interact, and live. Avanade is committed to good science, rigorous research methods, and the integration of AI in research workflows, helping clients see and create the future through applied research, experimentation, and collaboration.
Job Description: Quantitative Researcher, Innovation R&D
Join Avanade’s Innovation R&D team within the Office of the Chief Technology Officer (CTO) as a Quantitative Researcher. In this role, you’ll collaborate with the Head of Research and Head of Engineering to drive research initiatives, leveraging advanced statistical analysis, NLP, and predictive modeling. You will engage with cross-functional teams to explore emerging technologies, including Agentic AI, embodied AI, and quantum computing.
Key Responsibilities:
• Advanced Statistical Analysis: Conduct rigorous hypothesis testing, causal inference, and predictive modeling using Python.
• Natural Language Processing (NLP): Develop NLP models for text classification, sentiment analysis, and topic modeling.
• Survey Methodology and Psychometrics: Design and validate surveys, ensuring reliability and validity using psychometric techniques (e.g., factor analysis, IRT).
• Machine Learning Integration: Develop and implement machine learning models for social data analysis and predictive insights.
• Data Visualization and Reporting: Create compelling data visualizations and communicate findings to both technical and non-technical audiences.
• Research Design and Experimentation: Design experiments (A/B testing, quasi-experiments) to test hypotheses and evaluate digital experiences.
Skills and Experiences:
Technical Skills and Tools:
• Programming and Analysis: Proficiency in Python (SciPy, Statsmodels, NumPy, scikit-learn, TensorFlow, PyTorch) for data analysis, NLP, and predictive modeling.
• NLP and Machine Learning: Experience with Hugging Face Transformers, SpaCy, NLTK for NLP tasks, and advanced machine learning models for clustering, classification, and causal inference.
• Data Visualization and Collaboration: Strong skills in data visualization tools (Matplotlib, Seaborn, Plotly, Dash) and version control using GitHub and Jupyter Notebooks for effective collaboration.
Qualifications:
• Education: Master’s or PhD in Quantitative Psychology, Social Data Science, Computer Science, Data Analytics, or related fields.
• Experience: Proven experience in quantitative research, NLP, predictive modeling, and psychometrics.
• Academic or Professional Publications in relevant journals are highly valued.
Professional Skills:
• Advanced Statistical Analysis and NLP Expertise: Proficiency in hypothesis testing, causal inference, predictive modeling, text classification, sentiment analysis, and topic modeling using advanced NLP techniques.
• AI Integration and Workflow Optimization: Experience with integrating AI tools to enhance research workflows, improve efficiency, and maintain high-quality outputs.
• Communication and Collaboration: Strong problem-solving and critical thinking with a hypothesis-driven approach, coupled with excellent communication, cross-functional teamwork, and presentation skills for diverse audiences.
