Experienced Full Stack Data Scientist – Ads Data Solutions Research
At arenaflex, we're on a mission to revolutionize the way we understand and interact with our audiences. As a leader in the entertainment industry, we're constantly pushing the boundaries of innovation and creativity. Our team of data scientists plays a critical role in empowering our decision-makers with insights, predictions, and visualizations that shape the stories of hundreds of thousands of customers worldwide. We're seeking an experienced full stack data scientist to join our Ads Data Solution Research team. As a lead data scientist, you'll partner closely with cross-functional business partners to develop models for tackling complex challenges, including revenue, inventory, delivery, outcome, pricing, and more. If you're a seasoned analytical and modeling expert with a passion for driving impact, we want to hear from you.
About arenaflex
arenaflex is a global leader in the entertainment industry, with a rich history of innovation and creativity. Our company is built on a foundation of imagination, courage, and a commitment to excellence. We're proud to be a place where talented individuals from diverse backgrounds come together to create magic.
Job Responsibilities
As a lead data scientist in our Ads Data Solution Research team, you'll be responsible for:
- Modeling: Design, build, and enhance machine learning models to drive business outcomes. Work closely with engineering teams to develop and deploy models, and drive experimentation to test the impact of model-based optimization.
- Deep Analysis: Develop a deep understanding of audience, brand, and ad operational data systems and metrics. Mine large datasets to identify opportunities for revenue growth, viewer ad experience, and subscriber acquisition and retention.
- Visualization of Complex Data: Develop prototype solutions, mathematical models, algorithms, and strong analytics to communicate actionable insights clearly and visually.
- Partnership: Partner closely with business stakeholders to identify and unlock opportunities, and with other data teams to enhance platform capabilities around data modeling, data visualization, experimentation, and data architecture.
What You'll Bring
*
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 knowledge solutions
7+ years of experience
with statistical programming languages (e.g. Python, Spark, PySpark) and database languages (e.g. SQL)
Nice-to-Haves
*
Doctorate's degree
in a quantitative field
Excellent analytical skills
, superior level of data knowledge
Strong knowledge
of Python and libraries such as sci-kit-learn, SciPy
Familiarity
with Bayesian modeling and probabilistic programming applications such as PyMC
Familiarity
with data structures and programs such as Databricks, Jupyter, Snowflake, Airflow, Github
Familiarity
with data exploration and data visualization tools such as Tableau, Looker
Demonstrated skills
in choosing the right statistical tools given a data analysis problem
Ability to adapt quickly
in a fast-paced environment with shifting priorities
Strong communication skills
, both technical and non-technical audiences
Ability to manage multiple tasks
simultaneously and in a timely manner, including large and complex ones
Demonstrated management experience
, including people and project management
What We Offer
* Competitive salary: $25-45/Hour
- Flexible work environment: Work from home (WFH) opportunities available
- Opportunities for growth: Career growth opportunities and learning benefits
- Collaborative culture: Collaborative and dynamic work environment
- Recognition and rewards: Recognition and rewards for outstanding performance
How to Apply
If you're a seasoned data scientist with a passion for driving impact, we want to hear from you. Apply now to join our Ads Data Solution Research team and be part of a global leader in the entertainment industry. Apply Job! Apply for this job