Christopher Peter Makris Résumé
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98-01 67 th Avenue, Apt. 6 O, Rego Park, NY 11374 | p: (914) 882-5114 | e: [email protected] | LinkedIn C H R I S T O P H E R P E T E R M A K R I S S U M M A R Y Experienced Data Scientist combining a master’s degree in statistical practice with professional experience in data analysis and evaluation. Skilled at analyzing complex data sets and delivering simplified insights to influence strategic decision-making and product development. Technical competencies include: § Advanced R § Machine Learning § Team Management § Insight Generation § Applied Statistics § Experimental Design § Data Modeling § Algorithm Design § Probability Theory § Business Strategy § Metric Development § Social Data Mining P R O F E S S I O N A L E X P E R I E N C E NEW YORK CITY DATA SCIENCE ACADEMY, New York, NY May 2015 – Present Director of Data Science, Machine Learning Specialist / Quantitative Analyst § Operational Lead and Instructor in charge of directing training programs for an intensive 12-week bootcamp program focusing on programming, data science, data engineering, and project consulting. § Designs and delivers lectures on topics including machine learning, statistics, probability theory, data science, and programming in R to a student body of Master’s and PhD level graduates as well as former Executives. § Manages a team of Instructors, Teaching Assistants, and Interns in the delivery of lectures, review of curriculum, and tasking of administrative duties related to the student body. § Structures and delivers corporate data science training programs aimed at enhancing corporate clients’ (e.g., Aetna, Barclays, Department of Education, etc.) ability to make data-driven business decisions. § Participates in strategic consulting projects including the redesign of the bootcamp curriculum and enhancement of student relations that helped increase enrollment by 110%. § Created a detailed program that intertwines statistical and machine learning theory with applied practice by leveraging corporate client relationships to provide students with active projects. § Invited to present on Python programming and R machine learning at the CEWIT Conference, hosted by Stony Brook University and attended by over 475 professionals in the information technology field. MSLGROUP, New York, NY October 2013 – May 2015 Senior Digital Analyst / Digital Analyst / Account Executive § Evaluated analytics gathered through web and social media channels to strengthen campaign performance for various Procter & Gamble (P&G) product lines (e.g., Bounty, Charmin, Puffs, etc.). § Promoted to Senior Digital Analyst in 1 year and tasked with building a team of both Junior Analysts and Interns responsible for assessing social media data and developing reports based on detailed customer segmentations. § Created a model to calculate the tipping point for when a social media marketing campaign would go viral in order to allow the marketing team to determine the correct time to convert to paid media. § Pitched and taught implementation of the aforementioned model to the executive team, illustrating the value of data analytics in driving strategic business decisions and generating additional revenue. § Monitored and analyzed brands’ social media presences and content mixes in terms of trends, relevance, and engagement in order to inform strategic competitive positioning. § Mined unstructured data using Brandwatch and Radian6 to deliver insights and present recommendations. § Selected to author an article on big data mining in the global publication Critical Conversations. § Given a “Talent DNA” award directly from the CEO for recognition of high-level strategic thinking in client service delivery.
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Transcript of Christopher Peter Makris Résumé
98-01 67th Avenue, Apt. 6 O, Rego Park, NY 11374 | p: (914) 882-5114 | e: [email protected] | LinkedIn
C H R I S T O P H E R P E T E R M A K R I S
S U M M A R Y
Experienced Data Scientist combining a master’s degree in statistical practice with professional experience in data analysis and evaluation. Skilled at analyzing complex data sets and delivering simplified insights to influence strategic decision-making and product development. Technical competencies include: § Advanced R § Machine Learning § Team Management § Insight Generation § Applied Statistics § Experimental Design § Data Modeling § Algorithm Design § Probability Theory § Business Strategy § Metric Development § Social Data Mining
P R O F E S S I O N A L E X P E R I E N C E
NEW YORK CITY DATA SCIENCE ACADEMY, New York, NY May 2015 – Present Director of Data Science, Machine Learning Specialist / Quantitative Analyst
§ Operational Lead and Instructor in charge of directing training programs for an intensive 12-week bootcamp program focusing on programming, data science, data engineering, and project consulting.
§ Designs and delivers lectures on topics including machine learning, statistics, probability theory, data science, and programming in R to a student body of Master’s and PhD level graduates as well as former Executives.
§ Manages a team of Instructors, Teaching Assistants, and Interns in the delivery of lectures, review of curriculum, and tasking of administrative duties related to the student body.
§ Structures and delivers corporate data science training programs aimed at enhancing corporate clients’ (e.g., Aetna, Barclays, Department of Education, etc.) ability to make data-driven business decisions.
§ Participates in strategic consulting projects including the redesign of the bootcamp curriculum and enhancement of student relations that helped increase enrollment by 110%.
§ Created a detailed program that intertwines statistical and machine learning theory with applied practice by leveraging corporate client relationships to provide students with active projects.
§ Invited to present on Python programming and R machine learning at the CEWIT Conference, hosted by Stony Brook University and attended by over 475 professionals in the information technology field.
MSLGROUP, New York, NY October 2013 – May 2015 Senior Digital Analyst / Digital Analyst / Account Executive
§ Evaluated analytics gathered through web and social media channels to strengthen campaign performance for various Procter & Gamble (P&G) product lines (e.g., Bounty, Charmin, Puffs, etc.).
§ Promoted to Senior Digital Analyst in 1 year and tasked with building a team of both Junior Analysts and Interns responsible for assessing social media data and developing reports based on detailed customer segmentations.
§ Created a model to calculate the tipping point for when a social media marketing campaign would go viral in order to allow the marketing team to determine the correct time to convert to paid media.
§ Pitched and taught implementation of the aforementioned model to the executive team, illustrating the value of data analytics in driving strategic business decisions and generating additional revenue.
§ Monitored and analyzed brands’ social media presences and content mixes in terms of trends, relevance, and engagement in order to inform strategic competitive positioning.
§ Mined unstructured data using Brandwatch and Radian6 to deliver insights and present recommendations.
§ Selected to author an article on big data mining in the global publication Critical Conversations. § Given a “Talent DNA” award directly from the CEO for recognition of high-level strategic thinking in
client service delivery.
ATTENTION GLOBAL, New York, NY September 2012 – October 2013 Statistical Analyst
§ Led activities to compile and analyze social media data supporting the development of marketing, financial, and business products for the advertising agency’s various clients.
§ Served as a client-facing lead on the Mattel account, developing data-based statistical products for major brand segments (e.g., Barbie, Monster High, Scrabble, UNO, etc.).
§ Utilized raw and unstructured data gathered from social channels through Tracx and NetBase to inform strategic business decisions.
§ Conducted competitive audits to gauge competitor activity and influence in the social sphere using data to maximize brands’ positioning among target demographics.
CARNEGIE MELLON UNIVERSITY, Pittsburgh, PA August 2008 – May 2012 Teaching Assistant: Department of Statistics / Department of Mathematics
§ Designed and led lectures; evaluated exams, labs, and assignments for over 20 courses including: Experimental Design, Statistical Visualization, Multivariate Calculus, and Discrete Mathematics.
E. & J. GALLO WINERY, Modesto, CA May 2010 – August 2010 Intern: Statistical Consultant
§ Utilized regression methodology to predict wine temperatures throughout interstate transit. § Implemented cluster analysis to assess quality control and identify error types of product cappings.
AEGISTECH INC., New York, NY May 2009 – August 2009 Intern: Product Management
§ Evaluated MadCap Flare as a proof of concept for web publication and documentation of the automated stock trading platform Athena; delivered a business case for product purchase.
E D U C A T I O N & T R A I N I N G
CARNEGIE MELLON UNIVERSITY, Pittsburgh, PA May 2012 Master of Statistical Practice | GPA: 4.0 Graduate Consulting Thesis: Differentiating Types of Aphasia: A Case Study in Modern Data Mining Techniques
§ Identified multidimensional structure using principal component analysis, decision trees, random forests, and spectral clustering to derive new and verify old groupings of aphasia ailment types.
§ Assessed the reliability of and correlations among clinician and physician diagnoses. CARNEGIE MELLON UNIVERSITY, Pittsburgh, PA May 2011 Bachelor of Science: Statistics | Humanities Scholars Program | Major GPA: 4.0 Minor in Logic: Information & Computation | Minor GPA: 4.0 Minor in Discrete Mathematics | Minor GPA: 4.0 Senior Honors Thesis: Exploration of Imputation Methods for Missingness in Image Segmentation
§ 1st Place Oral Presentation, Meeting of the Minds 2011. § Derived unique segmentation methodology using cluster analysis and semi-supervised statistical
learning to impute and restore missing pixels in damaged images. Undergraduate Honors Research & Consulting Project: Task Assessment of Fourth and Fifth Grade Teachers
§ 1st Place Poster Presentation, Meeting of the Minds 2010. § Used generalizability and decision theory to assess teachers’ assignment quality. § Recommended varied combinations of tools and raters necessary to yield any desired grade reliability.
H O N O R S & A W A R D S
World Quantitative & Science Scholarship Senior Leadership Recognition Award
Inductee: Cum Laude Society College & University Honors
Inductee: Phi Kappa Phi Humanities Scholar
