Job Description

Data Scientist to support the development and enhancement of a newly established Smart Center in the Distribution Power Division which aims to monitor, automate, and analyze all smart devices within the Distribution Infrastructure which includes smart electricity meters, electric vehicle charging stations and distributed solar. The Data scientist is to support fetching information from various sources and analyze it to get a clear understanding of (confidential company's) distribution power infrastructure performance through the Smart Center. He/she needs to understand and use statistical and analytical methods plus AI tools to automate specific processes within (confidential company's) and develop smart solutions to business challenges. The scientist should be able to interpret data and analyze big data, and present the results in a clear and interesting way over dashboards and automated reports. The scientist should be able to analyze trends to support (confidential company's) management in making better decisions.

Roles and responsibilities:

Data mining or extracting usable data from valuable data sources

Using machine learning tools to select features, create and optimize classifiers

Carrying out preprocessing of structured and unstructured data

Enhancing data collection procedures to include all relevant information for developing analytic systems

Processing, cleansing, and validating the integrity of data to be used for analysis

Analyzing large amounts of information to find patterns and solutions

Developing prediction systems and machine learning algorithms

Presenting results in a clear manner

Propose solutions and strategies to tackle business challenges identified for the Smart Center for Distribution Power

Collaborate with Business and IT teams

Key Skills needed

Programming Skills - knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig. Familiarity with Scala, Java, or C++.

Statistics - Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential.

Machine Learning - good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests.

Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the fundamentals of Multivariable Calculus and Linear Algebra for predictive performance or algorithm optimization techniques.

Data Wrangling - proficiency in handling imperfections in data.

Experience with Data Visualization Tools using TIBCO Spotfire (essential), and other tools such as matplotlib, ggplot, d3.js., Tableau.

Excellent Communication Skills

Strong Software Engineering Background

Hands-on experience with data science tools

Problem-solving aptitude

Analytical mind and great business sense

Degree in Computer Science, Engineering or relevant field is preferred

Proven Experience as Data Analyst or Data Scientist (Min 10 years of experience)

Job Types: Full-time, Permanent, Contract