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Sam Mfalila
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Short Bio
Sam Mfalila is a Financial/Data Analysis professional with background in data science (Python, SQL, SAS), financial modeling, accounting, statistics, and strategic planning and analysis within telecom. Throughout his career, he has been privileged to work for different high performing teams and gained valuable practical insights on what keeps high performing organizations afloat and how data analytics enable these organizations take advantage of those insights. He has held different analytical roles with Verizon, providing expert testimony backed with data to aid management improve decision making and processes.

Data science combines his passion for applying the scientific method to solve business problems through making use of physical modeling, digital analytics, data engineering, and machine learning and AI to support strategic planning in business. At Verizon, Sam has used his domain knowledge in data science techniques such as predictive analytics, clustering, and machine learning to solve business problems in astonishing ways. For example, Sam has employed creativity in situations where data is not readily available by scrapping web data and parsing HTML code to accomplish analysis objectives by providing answers and insights to real business challenges. Sam has employed advanced data science methods such as machine learning and AI to develop insights to new questions and problems.

Sam is looking to contribute to organizational growth by finding different ways of solving practical business challenges through leveraging opportunities from data growth and digital analytics by implementing big data tools and technologies to help business managers understand impactful parameters to get the best ROI.
My Web Site Or LinkedIn Profile
http://www.linkedin.com/in/sammfaliladatascience
Field of Expertise
Data Science, Machine Learning, AI, Business Analytics, Deep Learning, Blockchain, BI, IoT
Professional Status
Consultant
Your Company:
VZ
Your Job Title:
Analyst
Interests:
Contributing, Networking
What is your Favorite Data Mining or Analytical Website?
http://https://www.datasciencecentral.com

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