Sijana Mamos Behavioural & Data Scientist People Operations Leader

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I'm a data-driven professional combining a unique blend of analytical expertise from both business and academic contexts. With an MSci in Cognitive and Decision Sciences from UCL and a background in Human Sciences from Oxford, I bring a strong foundation in computational modeling, statistics, and human behavior analysis to the field of data science.

In my roles leading People Operations and Talent Acquisition, I've consistently leveraged data analytics to drive decision-making—from developing predictive workforce models to conducting comprehensive analyses of hiring outcomes against performance metrics.

Currently, I'm deepening my technical expertise through intensive study in Data Science and Machine Learning, including comprehensive coursework in Python, TensorFlow, SQL, and various ML frameworks. My academic projects have included developing a Prisoner's Dilemma game using Python and Django, and working with neural networks and computational modeling.

I'm passionate about combining my understanding of human decision-making with technical data science skills to solve complex problems. My background in both people operations and cognitive science gives me a unique perspective on data analysis, allowing me to bridge the gap between technical solutions and human-centered outcomes.

Education

University of Oxford

BA Human Sciences, 2:1

Advanced Quantitative Methods (SPSS) and Computational Neuroscience.

University College London

MSc Cognitive & Decision Sciences, Distinction

Principles of Cognition, Statistics, Cognitive Science, Computer Programming (Python)

Neuromatch Academy

Computational Neuroscience

Neural Networks, Deep Learning in Python

Areas of Expertise

Data Science & Programming

Proficient in Python and Data Science libraries, comfortable with HTML, CSS, JavaScript, experience in statistical & data analysis (SQL, R).

Main interests: Machine Learning, Data Visualisation & Storytelling, NLP, CNN.

Operational & Team Leadership

8+ years experience in building and leading international Talent Acquisition & Operations teams across EMEA.

Implemented new operational functions for small and mid-size companies within professional services.

Behavioural Science & Organisational Design

In-depth understanding of employee behaviour and organisational design for operational, commercial and tech teams.

Experience in application of Behavioural Economics to enhance employee experience, performance & retention.

Featured Projects

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People Operations Portfolio

  • Data Analysis, Predictive Modelling, Project Management, Excel, Tableau, Plotly

A summary of key initiatives and tools I worked on as a Talent Acquisition & People Operations Leader: leadership initiatives, Talent Management frameworks and People Ops Analytics & Project Management tools adapted for non-technical teams.

Portfolio Website
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TV Show Data Analysis

  • Data Analysis, Visualisation, Python, Pandas, Matplotlib, Seaborn.

Used Friends' scripts and IMBD data to create data insights using Python, NLP techniques, data visualisation tools and Jupyter Notebooks.

GitHub Repo Medium Article
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Friends Nonsense Conversation Generator

  • Python, Deep Learning, Streamlit, GitHub Releases, API Integration

This app generates conversations between characters from the TV show *Friends*. Customize conversations with characters, catchphrases, and unique contexts.

GitHub Repo App Deployment
cnn-networks

Art Style Classifier Using CNN

  • Convoluted Neural Networks, Deep Learning, PyTorch, TensorFLow, Streamlit

A Classifier model using ResNet50 and Deep Learning, trained on WikiArt dataset to classify images into one of four art styles.

GitHub Repo App Deployment
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Fullstack Notion Clone

  • TypeScript, JavaScript, React, Full-Stack

Notion Clone using Next.js 13, React, Convex, Tailwind. Includes a real-time database, Notion-style editor, authentication, file management, page management and deletions.

GitHub Repo App Deployment
dashboard

Employee Data Dashboard

  • Plotly, Dash, Flask, Data Analysis, Machine Learning

A dashboard to analyse employee data and generate insights about performance and salary, including Machine Learning insights on predictors of performance.

GitHub Repo App Deployment

Tech Stack

Hobbies

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Travel

Avid traveller, visited over 40 countries across 4 continents.

Completed an around the world trip in 4 months, covering almost 60,000km. Check it out on my Polar Steps.

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Art

Drawing (architecture, dry pastels, digital art).

Other media: cross-stitching, calligraphy, pottery, photography.

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Fitness

Aerial sports (pole/hoop/silks) and weight-lifting enthusiast.

I also regularly practice yoga and reformer pilates.

Github LinkedIn Medium