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Data Scientist

MedReview Inc.
New York, NY
Full-time
AI tools:
TensorFlow
PyTorch

Position Summary: 

MedReview is looking for a talented and experienced Data Scientist to join our dynamic team. As a part of our team, you will leverage your analytical skills and expertise in machine learning to extract insights from complex datasets and drive data-driven decision-making across our organization. You will collaborate closely with cross-functional teams to develop predictive models, uncover actionable insights, and solve challenging business problems. As part of a global team of developers and analysts, the Data Scientist will work with a larger team to design, build, validate, refine, and operationalize models.

Responsibilities:

* Problem Identification: Collaborate with stakeholders to identify business challenges that can be solved through data analysis.

* Data Collection & Preparation: Gather data from various sources (SQL databases, APIs, web scraping), then clean and "wrangle" it to ensure accuracy for modeling.

* Model Development: Design and implement algorithms and predictive models using machine learning techniques to forecast outcomes or categorize information.

* Exploratory Data Analysis (EDA): Analyze datasets to uncover hidden patterns, trends, and anomalies.

* Communication & Visualization: Translate technical findings into "data stories" using tools like Tableau or Power BI to influence executive decisions. 

Qualifications: 

* Master’s degree or bachelors degree and equivalent experience in a quantitative field (Math, CS, Stats)

* Programming: Proficiency in Python or R  along with SQL for database querying.

* Mathematics & Statistics: Strong foundation in linear algebra, calculus, and statistical modeling.

* Machine Learning: Experience with frameworks like TensorFlow, PyTorch, or scikit-learn.

Soft Skills: Critical thinking, curiosity, and the ability to explain complex concepts to non-technical audiences. Experience working with global and remote teams

Applications go to the hiring team directly