Company Profile:

At Ericsson you’ll have a unique opportunity. The chance to use your skills and imagination to push the boundaries of what’s possible. To create never-seen-before solutions to some of the world’s toughest problems. You’ll be challenged. But you won’t be alone. You’ll be part of a team of like-minded innovators, all driven to go beyond the status quo to build what comes next. At Ericsson you can be an explorer, a change maker and a force for good.

Job description:

About this opportunity

Data Scientist acquires skills such as programming, communication, organizational, mathematical, data analysis, problem solving, and analytical skills.

What you will do

Handling Data science leadership

Predictive & Prescriptive Analytics, Web Analytics, Parametric and Non-parametric models, Regression, Time Series, Dynamic/Causal Model, Statistical Learning, Guided Decisions, Topic Modeling

Handling data question(s) by synthesizing

Be a coach for other Data Scientists

Able to Develop Data Science Infrastructure & Tools

Able to Convert data into concrete insights

Handling external relations

Able to Participate in external data science collaborations!

Ability to write robust code in Python, PySpark

Ability to work in a team

You will bring

Bachelor's -2 years in Data Science or Masters with 1 years in Teradata, SQL and relational databases, data warehouse or Ph.D. in Comp Science, Statistics, Mathematics.

Experience in statistical learning

Casandra, Postgres and query building

Design Principles, Application development, Flask, RESTful API,

Familiarity with GCP, Real time data ingestion!

Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)

Propose data science solutions, EDA, Model Prototyping, Visualization of the data, Interpretation of the data, results based on the requirement analysis

Outstanding analytical and problem-solving skills

Lead role mentoring multiple Jr. Analysts on approach and results.

Forecasting, Classification, Text Mining, NLP, Decision Trees, Adaptive Decision Algorithms, Random Forest, Search Algorithms, Neural Networks, Deep Learning Algorithms