Data Scientist

About Sugar.fit

Founded in 2021 Sugar.fit provides a personalized evidence-based path to type 2 and

pre-diabetes reversal and management. Sugar.fit leverages a precision health platform

combining CGM sensors, machine learning, and medical science to improve human

metabolic health and reverse chronic disease through precision nutrition, progressive fitness,

and behavioral health advice. Our research-driven treatment plan includes innovative

technology, compassionate diabetes experts, and personalized plans, which will help to lead

a normal life once more.

Function

Responsibilities:

● Quick Learners.

● Prior knowledge of ReactJS is a must.

● Comfortable with "Build fast and iterate".

● Project members at Sugarfit don't own code.

● Analyze raw data: assessing quality, cleansing, and structuring for downstream

processing.

● Design accurate and scalable prediction algorithms.

● Collaborate with the engineering team to bring analytical prototypes to production.

● Generate actionable insights for business improvements.

Requirements:

● Strong problem-solving skills with an emphasis on product development.

● Experience using statistical computer languages (R, Python, SLQ, etc. ) to

manipulate data and draw insights from large data sets.

● Knowledge of a variety of machine learning techniques (clustering, decision tree

learning, artificial neural networks, etc. ) and their real-world advantages/drawbacks.

● Excellent written and verbal communication skills for coordinating across teams.

● A drive to learn and master new technologies and techniques.

● At least 3 years of experience in quantitative analytics or data modeling.

● Deep understanding of predictive modeling, machine learning, clustering and

classification techniques, and algorithms.

● Fluency in a programming language (Python, C, C++, Java, SQL).

● Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop,

Spark, Tableau).