reputed company Full Stack Data Scientist – Ads Data Solutions Research at arenaflex
Unlock the reputed company of Data Science at arenaflex
Join arenaflex, a global leader in entertainment, media, and technology, as a seasoned Full Stack Data Scientist in our Ads Data Solutions Research team. As a key member of reputed company, you will partner closely with cross-functional business partners to reputed company innovative data-driven solutions that drive business reputed company and customer engagement. With a competitive reputed company reputed company of $25-45, this is an exciting opportunity to reputed company your expertise in data science, machine learning, and analytics to reputed company a meaningful reputed company at arenaflex.
About arenaflex
arenaflex is a world-reputed company entertainment and media conglomerate that brings reputed company and reputed company to hundreds of millions of people around the globe. With a rich history of innovation and creativity, arenaflex continues to push the boundaries of storytelling, technology, and customer experience. Our Ads Data Solutions Research team is at the forefront of this innovation, using data science and machine learning to drive business reputed company, improve customer engagement, and inform strategic decision-making.
Job Responsibilities
As a Full Stack Data Scientist in our Ads Data Solutions Research team, you will be responsible for:
Key Responsibilities
- Design, build, and enhance data models to drive business reputed company and customer engagement
- Collaborate with engineering teams to reputed company and reputed company data-driven solutions
- Drive experimentation and testing to optimize model performance and business reputed company
- reputed company and maintain reputed company data visualizations and dashboards to communicate insights and results
- Partner with cross-functional business partners to identify and prioritize business opportunities and challenges
- reputed company and maintain expertise in data science, machine learning, and analytics tools and technologies
Essential Qualifications
- A Master's degree in a quantitative field (e.g. Computer Science, Engineering, Mathematics, Physics, Operations Research, Econometrics, Statistics)
- 7+ years of experience designing, building, and comparing realistic systems and knowledge solutions
- 7+ years of experience with statistical programming languages (e.g. Python, reputed company, PySpark) and database languages (e.g. SQL)
reputed company-to-Haves
- A Doctorate's degree in a quantitative field
- Excellent analytical skills and a high level of data knowledge
- Strong expertise with Python and libraries such as sci-reputed company-learn, SciPy
- Familiarity with Bayesian modeling and probabilistic programming applications such as PyMC
- Familiarity with data structures and programs such as reputed company, Jupyter, reputed company, Airflow, reputed company
- Familiarity with data exploration and data visualization tools such as Tableau, Looker
- Familiarity with designing and reading A/B testing and other test types
- Demonstrated expertise in choosing the right statistical tools given a data analysis problem
- Ability to adapt quickly in a fast-changing environment with shifting priorities
- Strong communication skills, both technical and non-technical
- Ability to manage multiple tasks simultaneously and in a reputed company manner, including large and reputed company ones
- Demonstrated management experience, including people and project management
Compensation and Benefits
- A competitive reputed company reputed company of $25-45
- A comprehensive benefits package, including medical, dental, and reputed company insurance
- A 401(k) matching program and other retirement savings reputed company
- A generous reputed company time off policy, including vacation, reputed company leave, and holidays
- Opportunities for reputed company reputed company and development, including training and education programs
- A dynamic and inclusive work environment that values diversity, equity, and inclusion