Find probable features and further needs of inputs Feature engineering and feature selection or engineering network architecture Selection of hypothesis set and evaluation of alternatives.
Participate in understanding and brainstorming a business scenario and available data to arrive at a hypothesis.
Use case creation from data, understand the architectural impacts of proposed use cases. Scope and identify success criteria and inputs needed for the analysis. Data sources and approaches for wrangling data and creation of data pipelines.
Introduce new employees to available data infrastructure. improve data science experiments to fully available resources. Investigate and explore new possibilities.
Participate in the evolution of data science infrastructure and tools for Ericsson Data Science environments.
Be the main author to external publications to demonstrate Ericssons technical leadership for customers and research society.
You will bring
Forecasting, Classification, Data/Text Mining, NLP, Decision Trees, Adaptive Decision Algorithms, Random Forest, Search Algorithms, Neural Networks, Deep Learning Algorithms.
Predictive Prescriptive Analytics, Web Analytics, Parametric and Non-parametric models, Regression, Time Series, Dynamic/Causal Model, Statistical Learning, Guided Decisions, Topic Modelling
Experience with big data analytics - identifying trends, patterns, and outliers in large volumes of data.
Ability to write robust code in Python, PySpark and Kubernetes, Docker, Spark.
Familiarity with GCP, Real time data ingestion
Propose data science solutions, EDA, Model Prototyping, Visualization of the data, Interpretation of the data, results based on the requirement analysis.
Must Have Skill
Minimum 5+ years of Relevant experience as a data Scientist or Total 8 to 15 years of experience as Developer and Data scientist.
Data Science, Machine Learning and Artificial Intelligence.
Worked with Gen AI, LLM and Prediction Models
Development as well as Deployment in live environment
