Senior Data Science Researcher
Stardat is a subsidiary of UST Global, serving as the company’s central advanced analytics and data science arm. UST Global is an American multinational provider of Digital, IT services and solutions which serves many top Fortune-500 companies.
We use cutting-edge technologies and state-of-the-art machine-learning algorithms to supply our customers with data science solutions to increase their revenues. We are currently looking for a new member to join our emerging team as a Senior Data Science Researcher.
If you consider yourself a team player who likes to share ideas and brainstorm with others, a highly creative person who enjoys solving complex problems, self-driven with the ability to learn and master new fields, we would love to hear from you.
What you will be doing:
- Conduct research to find, develop and improve algorithmic solutions to a variety of ML problems in different fields (NLP, computer vision, recommendation systems, predictive maintenance and more).
- Collaborate with team members and stakeholders to effectively manage the lifecycle of project.
- Work on end-to-end machine learning projects including design, data processing, feature engineering, model selection, training and testing.
- Explore the market and the existing solutions in the industry for problems we need to solve.
- Engage with customers to frame their problems, translating from a general business pain to a measurable scientific problem. Define objectives, KPI’s and API’s for the proposed solutions.
- Interpret and communicate findings and insights from the data to business partners.
Desired qualifications and skills:
- MSc. Graduate in Computer Science / Mathematics / Electrical Engineering / Physics who graduated with honors (PhD in these areas – an advantage)
- At least 3 years of experience as a practicing data scientist with at least 5 years in the computer science industry.
- Good python programing skills
- Experience with the data science lifecycle, including data engineering, feature engineering, model building and evaluation, model deployment.
- Understanding of data science/machine learning models and algorithms, including (but not limited to): deep learning (CNN, RNN, etc.), decision trees, unsupervised techniques (e.g. clustering, anomaly detection), Computer Vision, Natural Language Processing and statistical methods.
- Ability to synthesize complex information into clear insights and translate those insights into decisions and actions.
- Strong analytical skills, attention to detail and accuracy.
- Strong mathematical orientation.
- Excellent problem-solving skills and creative thinking ability.
- A great team player with a can-do approach.
- Willingness to impact beyond defined role.
- Desire to get things done and seek better ways to do the job
- High level of English communication (verbal and written)