LESS DATA, MORE STORIES

Reasons to trust LDMS

Proven Track Record –> years of experience in teaching data science and applying these skills in real-world scenarios.

Practical Expertise –> with a strong background in data science, improv and creative writing, I bring a unique perspective to make learning enjoyable and effective.

Interactive Approach –> workshops are not just about theory; they’re about hands-on learning, ensuring participants can apply their newfound knowledge.

Tailored Solutions –> I understand that every organisation is unique. My workshops and consulting services may be customised to fit your specific needs and objectives.

And the most important, I always try to keep a vibrant and positive environment where fun and professionalism go hand in hand. On top of these, you may find some examples of my previous experience below.

During my tenure at Amadeus, I played a pivotal role in a significant big data project in collaboration with American Airlines. The focus was on choice modelling within bookings and flight searches, aiming to enhance the customer experience by gaining profound insights into user preferences.

Challenges:

• Diverse Customer Preferences: American Airlines serves a broad customer base, each with distinct preferences.
• Complex Booking Patterns: Analysing intricate patterns in flight bookings and searches to tailor offerings.

Solution:
Leveraging my expertise in data science and machine learning at Amadeus, I dove into complex data sets, identifying trends in customer behaviour. This allowed American Airlines to personalise services based on individual preferences.

Outcomes:

• Personalised Offers: Implementation of personalised offerings significantly enhanced customer satisfaction.
• Streamlined Booking Experience: The insights from the analysis led to a more streamlined booking process, resulting in increased customer engagement and loyalty.
• Data-Driven Strategy: The findings became a cornerstone in Amadeus’ and American Airlines’ joint data-driven decision-making strategy.

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At YouGov Signal, I had the exciting opportunity to collaborate with Amazon Prime Video on a project to predict the popularity of new TV shows and movies. Using advanced machine learning models, our goal was to optimise content recommendations and enhance user engagement.

Challenges:

• Vast Content Library: Predicting user preferences accurately amidst the extensive content.
• Evolving Viewer Trends: Keeping pace with ever-changing viewer trends and preferences in the competitive streaming landscape.

Solution:
Drawing on my expertise in predictive modelling at YouGov Signal, I analysed historical data to develop models that accurately forecasted the popularity of new content based on various factors, including genre, cast, and viewer demographics.

Outcomes:

• Enhanced Content Recommendations: Implementation of predictive models improved content recommendations, leading to higher viewer satisfaction.
• Strategic Content Investments: Valuable insights from predictive models guided strategic content investments, maximising the impact of new releases.
• Increased Viewer Engagement: Predictive popularity assessments contributed to increased viewer engagement and longer retention on the platform.

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In addition to my hands-on industry experience, I have had the privilege of spending five fulfilling years teaching Data Science at KSCHOOL. Over the span of approximately 10 editions, I’ve had the opportunity to mentor and guide aspiring data scientists through a comprehensive curriculum covering Python, Shell scripting, machine learning, Spark, Google Cloud, and the art of data storytelling.

Challenges:

• Nurturing Diverse Talents: Catering to students with varying backgrounds and skill levels.
• Keeping Pace with Evolving Technologies: Ensuring the curriculum remains up-to-date and relevant in the rapidly changing field of data science.

Solution:
Drawing from my real-world experiences, I strived to create a dynamic and practical learning environment. My goal was not just to impart knowledge but to develop their problem-solving skills and a deep understanding of industry applications.

Outcomes:

• Diverse Skill Set: Students gained proficiency in Python, Shell scripting, machine learning, Spark, Google Cloud, and data storytelling.
• Positive Student Feedback: I am immensely proud of the many messages received from former students expressing gratitude for the practical skills acquired during the course.

Impact:
Several of my students have gone on to achieve remarkable success in the field of data science, building illustrious careers with leading organisations. Their accomplishments stand as a testament to the effectiveness of the curriculum and the practical skills imparted during their time at KSCHOOL.

These success stories underline my commitment to nurturing the next generation of data scientists and contributing to the success stories of individuals who have flourished in the field.

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