Data Scientist

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.

This position will sit in Austin, Texas. However, for the right fit, we may consider remote

.

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