As a Data Scientist, your expertise lies in comprehending both the technical and business facets of Data Analysis, Artificial Intelligence, and Machine Learning within the digital media industry. Your responsibility is to lead the execution of data science projects within the defined scope, while also anticipating and handling unforeseen DS/AI/ML needs in a dynamic setting.
Responsibilities Overview:
- Collaborate with business stakeholders to gather, examine, and transform business goals into problem statements for data science, artificial intelligence (AI), and machine learning (ML) projects.
- Convert problem statements in data science into technical specifications by defining calculations, custom groups, parameters, filtering criteria, aggregations, clusters, and other relevant components.
- Coordinate with the data engineering team to collect, process, cleanse, and validate multivariate data from internal or external systems, adhering to the technical specifications.
- Choose features, optimize classifiers, perform statistical analysis, develop diverse data models using machine learning techniques to identify data patterns and trends, and generate actionable insights and key performance indicators (KPIs).
- Deliver insights through intuitive presentations, interfaces, infographics, and visualizations, effectively conveying the business implications to stakeholders andleadership in a clear manner.
- Leverage consumer behavior data to uncover innovative product insights, driving consumer engagement and revenue growth for the business.
- Assist in segmenting consumers, predicting churn, and constructing recommendation systems.
- Build automated anomaly detection systems and continuously monitor their performance.
- Conduct ongoing evaluations of machine learning technology solutions, ensuring alignment with business objectives, identifying potential risks, and identifying areas for improvement within the current environment.
Must Haves:
To be successful in this role, we require an individual with the following qualifications and skills:
- A minimum of 4 years of top-tier experience in Data Science/Machine Learning, and 7 years of experience in Data Analysis on cloud Infrastructure (predominantly AWS and preferred GCP), using languages such as R, Python, and SQL, among others.
- An excellent understanding of the practical application of machine learning techniques and algorithms, including k-NN, Naive Bayes, SVM, Decision Tree, Random Forests, and others.
- The ability to create, execute, and analyze complex AB/MVT test constructs to test hypotheses.
- Experience using Amazon SageMaker/Tensorflow/Google Cloud AutoML/Keras.
- Experience with Spark Streaming (Databricks) or other data science focused data processing platforms for real-time big data analytics.
- Familiarity with other data engineering tools and systems such as Snowflake, Airflow, Jenkins, Github, and others.
- Comfortable working in a fast-paced, high-tech environment (preferably in software development) and able to navigate conflicting priorities and ambiguous problems.
- Proficient with data visualization tools such as Looker and Tableau.
- Working knowledge of digital media ecosystems, including how digital video streaming, ad servers, DSPs, SSPs, Log analytics, and other related areas function.
- Possesses a data-driven mindset, with excellent communication and collaboration skills that enable interaction with technical and non-technical stakeholders.
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Last updated on May 16, 2023