Our guest today is a high-energy data science professional with the proven ability to rapidly prototype new machine learning techniques and deliver on feature requirements.
She’s an innovative data scientist who has coupled her visionary and conceptual thinking approach to develop statistical and machine learning models to create scalable NLP solutions that can be embedded within larger systems.
She’s got a knack for crafting clear arguments, stunningly coherent presentations, and uses her powers of persuasion to listen, influence, and network effectively.
Throughout her career she’s gained significant work experience in industry and applied research and has attained a series of academic accolades, including bachelors and masters degrees in Telecommunications Engineering from the Polytechnic University of Tirana as well as a PhD in Computer Science from the University of New York - where she developed a new algorithm called Randomized Greedy Ensemble Outlier Detection with GRASP.
Say that three times fast!
She’s worked at organizations such as the Canadian Institute of Technology and Klick.
She’s currently at Veeva Systems - where she develops models that leverage NLP and Machine Learning to help drive impactful insights and quickly identify, classify, and prioritize Adverse Drug Events.
She’s also a Data science mentor with Sharpest Minds, where she mentors and guides mentees in STEM fields that want to learn data science and NLP.
She’s a well known and respected member of Toronto Women of Data Science - where she lives out her passion for giving back to the community by helping and advising women break into the field of data science.
So please help me in welcoming our guest today - a woman whose recent honors include FIVE published papers across various academic journals - Dr. Lediona Nishani!
April 8th, 2020 | Season 1 | 33 mins 6 secs
ai, data science, grit, growth mindset, journey, machine learning, math, passion, persistence, statistics
Remove your self-limiting beliefs, unleash your inner spirit animal, and climb the ranks of the data science competence hierarchy