Data Scientist
Ericsson
Bangalore, KA, IN
15d ago

Ericsson Overview :

Ericsson is world’s leading provider of communications technology and services. Our offerings include services, consulting, software and infrastructure within Information and Communications Technology.

Using innovation to empower people, business and society, Ericsson is working towards the Networked Society : a world connected in real time that will open up opportunities to create freedom, transform society and drive solutions to some of our planet’s greatest challenges.

We are truly a global company, operating across borders in over 180 countries, offering a diverse, performance-driven culture and an innovative and engaging environment.

As an Ericsson employee, you will have freedom to think big and the support to turn ideas into achievements. Continuous learning and growth opportunities allow you to acquire the knowledge and skills necessary to progress and reach your career goals.

We invite you to join our team.

Position Summary : Purpose of the Job Role

Purpose of the Job Role

Responsible for developing scientific methods, processes, and systems to extract knowledge or insights to drive the future of applied analytics.

Provide thought leadership, perform Advanced Statistical Analytics, and create insights into data to provide to the business actionable insights, identify trends, and measure performance which address business problems.

Collaborate with business and process owners to understand business issues, and with engineers to implement and deploy scalable solutions, where applicable.

Responsibilities & Tasks :

  • Perform Data science leadership
  • Synthesize problems into data question(s)
  • Decide approach for data science
  • Design & perform data science experiment
  • Develop Data Science Infrastructure &Tools
  • Convert data into actionable insights.
  • Act in external relations
  • Job Summary

    As a data scientist the purpose of the role is to create principles, models and guidelines from strategies. Continuously convert requirements to cost efficient solution compliant to architectural principles, models and guidelines ensuring consistency between business, information and technology.

  • Post graduate degree in Statistics, Computer Science, Econometrics, Quantitative Marketing from top tier institutions in India and abroad
  • 3 years or more experience in data processing and analysis as preparation for data mining / predictive analytics requirements
  • 3 years or more experience in Predictive Analytics and Data Mining with at hands-on knowledge and experience in at least the following areas : -
  • Linear Regression Classification Techniques Logistic Regression Decision Tress including Random Forests Discriminant Analysis Support Vector Machines Unsupervised Learning techniques like k-

    means / hierarchical clustering Feature reduction methods like PCA, SVD

  • Knowledge of assumptions of above models and performing diagnostics
  • Experience in Optimization methods with at least knowledge of LP, IP, mixed IP programming techniques
  • Experience with working in R / Python. Nice to have SPSS Statistics / modeler experience.
  • Ability to read research papers to apply state-of-the-art methods into the business domain
  • Ability to contribute to research papers in journals / conferences to present output of the work
  • Experience on text mining problems
  • Strong written and oral communication skills
  • Nice-to-have requirements : -

  • Experience in model implementation on Big Data platforms including model parallelization across different nodes
  • Experience in machine learning applications of online scoring problems
  • Experience in stochastic optimization problems
  • Experience in social media analytics and graph based models
  • Education / Experience Required (In Years)

  • Post graduate in machine learning / statistics / econometrics from top-tier institutions in India or abroad. Strong quantitative MBA students can also apply.
  • Knowledge of various supervised and unsupervised machine language algorithms
  • Demonstrated experience in programming languages in R and at least one of SAS, SPSS, Matlab, Octave.
  • 5+ years of relevant experience.(negotiable)
  • Proven leadership and management skills.
  • Behavioral Competences

  • Learning and researching
  • Formulating strategies and concepts
  • Applying expertise and technology
  • Adapting and responding to change
  • Planning and organizing
  • Analyzing
  • MINIMUM QUALIFICATION AND EXPERIENCE REQUIREMENTS

  • A Master’s or higher degree in Computer Science, Statistics, Mathematics, or related disciplines
  • Evidence of academic training in Statistics
  • PREFERRED QUALIFICATION AND EXPERIENCE REQUIREMENTS

  • Deep / broad knowledge of machine learning, statistics, optimization, or related field
  • A genuine interest in new and applied technology and software engineering coupled with a high degree of business understanding
  • Any applied research contributions to the community in terms of technical papers and patents, are encouraged
  • Ericsson provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, marital status, pregnancy, parental status, national origin, ethnic background, age, disability, political opinion, social status, veteran status, union membership or genetics.

    Ericsson complies with applicable country, state and all local laws governing nondiscrimination in employment in every location across the world in which the company has facilities.

    In addition, Ericsson supports the UN Guiding Principles for Business and Human Rights and the United Nations Global Compact.

    This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, training and development.

    Ericsson expressly prohibits any form of workplace harassment based on race, color, religion, sex, sexual orientation, marital status, pregnancy, parental status, national origin, ethnic background, age, disability, political opinion, social status, veteran status, union membership or genetic information.

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