Data Scientist

Key Skills

Algorithms, Analytical and Problem solving, Clustering, Data science techniques, Database, Deep Learning, Effective communication skills, Large data sets, Machine learning techniques, Python Programming, R Programming, Random forests, SQL

Job Description

Here at ShyftLabs, we are searching for an experienced Data Scientist who can derive performance improvement and cost efficiency in our product through a deep understanding of the ML and infra system, and provide a data driven insight and scientific solution.

ShyftLabs is a growing data product company that was founded in early 2020, and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation.

Job Responsibilities:

Data Analysis and research: analyzing a large dataset with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could complete and improve a complex ML and bidding system.

Simulation and Modelling: validating and quantifying the efficiency and performance gain from hypotheses through rigorous simulation and modelling.

Experimentation and Causal Inference: developing a robust experiment design and metric framework, and providing reliable and unbiased insights for product and business decision making.

Basic Qualifications:

Master's degree in a quantitative discipline or equivalent.

3+ years minimum professional experience.

Distinctive problem-solving skills, good at articulating product questions, pulling data from large datasets and using statistics to arrive at a recommendation.

Excellent verbal and written communication skills, with ability to present information and analysis results effectively.

Ability to build positive relationships within ShyftLabs and with our stakeholders, and work effectively with cross-functional partners in a global company.

Statistics: must have strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.

Machine Learning: must have deep understanding of ML algorithms (i.e. deep learning, random forest, gradient boosted trees, k-means clustering, etc.) and its development, validation, and evaluation.

Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas).

We are proud to offer a competitive salary alongside a strong healthcare insurance and benefits package. The role is preferably hybrid, with 2 days per week spent in office. We pride ourselves on the growth of our employees, offering extensive learning and development resources.