Role and Responsibilities: As a Data Scientist at Comcast, you will play a pivotal role in designing, solutioning, and implementing data solutions while leveraging your analytical prowess to extract meaningful insights. You will also be responsible for presenting your findings to both technical and non-technical stakeholders and leading collaborative efforts within cross-functional teams.Your Key Responsibilities Include
Design, construct, install, and maintain data pipelines for optimal extraction, transformation, and loading (ETL) of data from various sources.
- Develop scalable and efficient data pipelines to facilitate the collection, storage, and processing of large volumes of structured and unstructured data.
- Apply advanced statistical analysis, machine learning, and data mining techniques to derive actionable insights from complex datasets.
- Develop and implement predictive, prescriptive and inferential models to solve business challenges and drive decision-making processes.
- Must be good with collaborating with technical and non-technical stakeholders to effectively understand the business challenge, use case and structure the discussion in succinct format for driving next steps.
- Collaborate with domain experts to understand business requirements and translate them into data-driven solutions.
- Communicate complex technical concepts and analytical findings effectively to both technical and non-technical stakeholders.
- Create visually compelling presentations, reports, and dashboards to convey insights and recommendations.
- Lead workshops, meetings, and discussions to drive alignment and understanding across teams.
- Provide strategic guidance and contribute to the development of data-driven strategies within the organization.
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
- Proven experience (6+ years) as a data engineer and data scientist, preferably in a fast-paced technology or analytics-driven environment.
- Experience in leveraging Graph data science concepts to solve business use cases a must.
- Strong proficiency in data engineering tools and languages (e.g., SQL, Python, Scala, ETL frameworks, data warehousing).
- Comfortable and experienced working in Databricks, Spark environment.
- Extensive experience with machine learning frameworks (e.g., TensorFlow, H2O) and data science libraries (e.g., SparkML).
- Ability to develop visualizations, as necessary to present insights, metrics and how this informs addressing the business challenge.
- Excellent presentation and communication skills, with the ability to convey technical concepts to non-technical audiences.
- Experience in a networking or communications domain is a plus.
- Experience interacting with other technical and non-technical stakeholders to collaborate on efforts like solutioning, understanding other data domains in order to source data is a must.