About the Company
Merck & Co. Inc., established in 1891, is a global research-driven pharmaceutical company dedicated to
putting patients first. Join us and experience our culture first-hand - one of strong ethics & integrity,
diversified experiences and a resounding passion for improving human health. As part of our global
team, you'll have the opportunity to collaborate with talented and dedicated colleagues while developing
and expanding your career.
About the Opportunity
The Research Associate in the Applied Mathematics and Modeling group develops statistical models and
computational solutions using large-scale data manipulation, statistical analyses, data mining,
visualization, and related analytical techniques aimed at improving specific scientific and business
decisions/processes. Example project areas include manufacturing process improvement, portfolio
planning, drug safety assessment, experimental design and analysis, biomarker discovery, and disease
modeling. The work is fast paced, innovative, and requires the efforts of a top tier data scientist.
Location: West Point, PA
Positions: 2 Full-time positions
To Apply: Go to https://merck.taleo.net/careersection/merck_external_career_section/jobsearch.ftl and
search for Job Numbers BUS000434 AND BUS000436. Please apply to BOTH full time opportunities.
Qualifications
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A PhD (or expected to earn a PhD within the next 6 months) OR a Master's Degree with at least
five years of data mining experience.
A degree in one of the following fields: computer science, computational biology, statistics, or
another computational area with an emphasis on the use of machine learning/data mining to build
predictive models.
Extensive hands on experience working with very large data sets, including statistical analyses,
data visualization, data mining, and data cleansing/transformation.
Under-the-hood knowledge of many of these machine learning concepts:
supervised/unsupervised learning, loss functions, regularization, feature selection,
regression/classification, cross-validation, bagging, kernel methods, graphical models, mixture
models, sampling, probability distributions, etc.
Experience prototyping and developing data mining solutions using statistical software packages
(R, Matlab, etc).
Strong Unix/Linux scripting skills (Perl, Python, etc).
Familiarity with writing SQL queries and working with databases.
Object oriented programming experience (Java, C++, etc).
Strong ability to communicate deep analytical results in forms that resonate with scientific and/or
business collaborators, highlighting actionable insights.
Entrepreneurial inclination to discover novel opportunities for applying analytical techniques to
business/scientific problems across the company.
Capacity to motivate and train junior scientists and offer counsel to peers.
Basic understanding of cell biology, genetics, or biochemistry in order to understand underlying
scientific problems/processes and to facilitate effective communication with scientific
collaborators is a plus.
Previous experience working with common biological R&D data streams (next generation
sequencing, gene expression, high-throughput screening, etc) is a plus.
Responsibilities:
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Lead the data acquisition, data mining, and overall project management duties related to one or
more existing analytics project areas.
Collaborate with scientific colleagues to define the data modeling goals for designated project
areas.
Plan and schedule daily computing, research and reporting activities in order to meet established
timetables and objectives.
Design and implement creative approaches to predictive modeling problems.
Perform model assessments, validation, and enhancement activities.
Collaborate with software developers to plan and construct the architecture surrounding model
deployment.
Maintain a working knowledge of data mining and visualization best practices.
Acquire any specialized domain knowledge required to be more effective in all required activities.
Communicate progress and results of program to scientific collaborators or management of
Merck Research Laboratory (MRL) by issuing periodic reports or preparing required documents
needed for regulatory approval of a compound.
Enhances individual and corporate reputation by publishing or presenting technical papers to
internal and/or external audiences and actively participating in professional societies, technical
associations, national standards committees, etc.
Makes significant and continuing contribution to developing novel quantitative projects.