Senior Data Scientist

Summary

The job is for a Senior Data Scientist in the Data Analytics Industry. The role involves transforming raw data into meaningful information, using machine learning tools, preprocessing data, analyzing large amounts of information, developing prediction systems and machine learning algorithms, providing mentorship, collaborating with stakeholders, and presenting results graphically. The required qualifications include at least 4-5 years of experience as a Data Scientist, knowledge of R, SQL, Python, Microsoft Azure Technology and Databricks or similar technology, data visualization & data wrangling experience, knowledge of machine learning methods and applied statistical skills.

Requirements

• At least 4-5 years of proven work experience as a Data Scientist
• Extensive experience in data mining, interpreting and cleaning data as well as in machine learning
• Knowledge of R, SQL and Python
• Working experience with Microsoft Azure Technology and Databricks or similar technology
• Data Visualization & Data Wrangling experience
• Very good knowledge of machine learning methods like k-Nearest, Neighbors, Naive Bayes, SVM, Decision Forests
• Very good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc

Responsibilities

• Transform raw data into meaningful information
• Data mining or extracting usable data from business data sources
• Use of machine learning tools to select features as well as create and optimize classifiers
• Preprocess of structured and unstructured data
• Enhance data collection procedures to include all relevant information for developing analytic systems
• Process, clean, and validate the integrity of data to be used for analysis
• Analyze large amounts of information to find patterns and solutions
• Develop prediction systems and machine learning algorithms
• Provide ongoing mentorship and coaching to data science team
• Propose solutions and strategies to tackle business challenges
• Work closely with stakeholders – internal and external, including business analysts, IT team, project managers, and data scientists. Collaborate with all stakeholders to understand their data needs and deliver solutions that meet them
• Present graphically the results of the process