Data Scientist (NYC, LA, SF or Seattle)
Onsite Hybrid role - 3 days a week
We are seeking a highly motivated and talented Senior Data Scientist to join our team of experts in developing and maintaining recommendation and personalization algorithms for Disney Streaming's suite of streaming video apps. As a member of our team, you will play a pivotal role in shaping the future of our streaming services by applying state-of-the-art machine learning methods to meet strategic product personalization goals.
• Algorithm Development and Maintenance:
o Utilize cutting-edge machine learning techniques to develop and enhance algorithms for personalization, recommendation, and predictive systems.
o Take ownership of maintaining and optimizing algorithms deployed in production environments.
o Serve as the point person for explaining methodologies to both technical and non-technical teams, fostering clear communication.
• Analysis and Algorithm Optimization:
o Conduct in-depth analysis of user interactions within our apps and user profiles to drive improvements in key personalization metrics.
o Collaborate with data scientists and engineers to refine algorithms and enhance their performance continually.
• MVP Development:
o Innovate and develop machine learning products that can be used for new production features or by downstream production algorithms.
o Work closely with cross-functional teams to prototype and operationalize personalization solutions.
• Development Best Practices:
o Maintain and establish best practices for algorithm development, testing, and deployment, ensuring high-quality code and efficient processes.
• Collaboration with Product and Business Stakeholders:
o Identify and define new personalization opportunities by collaborating with product and business stakeholders.
o Collaborate with other data teams to improve data collection, experimentation, and analysis methods.
Required Qualifications:
• 7+ years of analytical experience
• 5+ years of experience developing machine learning models and performing data analysis with Python and tensor-based model development frameworks (e.g. PyTorch, Tensorflow)
• 5+ years writing production-level, scalable code (e.g. Python, Scala)
• 5+ years of experience developing algorithms for deployment to production systems
• In-depth understanding of modern machine learning (e.g. deep learning methods), models, and their mathematical underpinnings for recommendation engines
• In-depth understanding of the latest in natural language processing techniques and contextualized word embedding models
• Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark
• Familiarity with data exploration and data visualization tools like Tableau, Looker, etc.
• Understanding of statistical concepts (e.g., hypothesis testing, regression analysis)
• Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick, effective solutions as appropriate
• Strong written and verbal communication skills
• Ability to explain how models are used and algorithms behave to both technical and non-technical audiences
Additional Preferred Qualifications:
• MS or PhD in computer science, data science, statistics, math, or related quantitative field
• Production experience with developing content recommendation algorithms at scale
• Experience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment
• Experience with graph-based data workflows such as Apache Airflow
• Experience engineering big-data solutions using technologies like EMR, S3, Spark, Databricks
• Familiar with metadata management, data lineage, and principles of data governance
• Experience loading and querying cloud-hosted databases such as Snowflake
• Familiarity with automated deployment, AWS infrastructure, Docker or similar containers
Flexible work from home options available.
Compensation: $140,000.00 - $160,000.00 per year
About Us
Triunity is a Product Development, Staff Augmentation, and Consulting Services company providing solutions and services in North America. We provide IT services and technology solutions to various business verticals like Healthcare, Pharma, Banking, Finance, etc. Our goal is to develop a long-term partnership with businesses and help them get a competitive advantage by providing IT infrastructure and software platforms.
Lead by experts in the IT industry with a proven record of delivering software solutions, consulting, and staffing services, we have expertise in fulfilling client needs in terms of customized business solutions as well as IT consulting. At Triunity, we always try to bring the right mix of skills, technologies, and experts together which helps our clients to stay ahead in the competition. Our goal is to make our clients empower with cutting-edge technologies and take care of all their IT needs so they can focus more on their core business.
Triunity Culture
Our core value is our people and our teams . We believe the real mantra of success is like minded people with right mix of technical and analytical skills. Our strength lies in bringing right set of people and delivering work as a team. Be it expert or intern Triunity always always value its own people and give them platform to excel in their career.
At Triunity you can expect
- Challenging & Friendly
- Work on new edge technologies & tools
- Work with industry experts
- Solving complex client problems and delivering solutions
- Working on projects lasting from six months to several years
Careers & Growth Model
At Triunity people are motivated by the complexity and challenges they face when working on client projects . We always motivate our people to keep learning new technologies and also give them platform where they can get chance to show their technical and analytical skills . We help our people in adding latest technologies ,tools, methodologies and certifications to their resume by arranging trainings , seminars and knowledge sharing sessions.
(if you already have a resume on Indeed)