Roles and Responsibilities

• Build data systems and pipelines for data collection. Combine raw information from different sources.

• Processing, cleansing, and validating the integrity of data to be used for analysis. Explore ways to enhance data quality and reliability

• Analyze huge amounts of data, both structured and unstructured raw data. Interpret trends and patterns.

• Conduct complex data analysis and report on results and present data using various data visualization techniques and tools.

• Prepare data for prescriptive and predictive modeling including machine learning models.

• Build algorithms and prototypes

• Identify opportunities for data acquisition

• Develop analytical tools and programs

• Continually improving coding skills

Skills and Qualifications:

• Degree in Computer Science, IT, or similar field; a Master’s is a plus

• Minimum 1 year experience as a data engineer/scientist or in a similar role

• Technical expertise with data models, data mining, and segmentation techniques.

• Ability to compose pipelines for data science models.

• Knowledge of Machine Learning techniques, including decision tree learning, clustering, artificial neural networks, etc., and their pros and cons

• Data Wrangling – proficiency in handling imperfections in data.

• Programming Skills – good knowledge of statistical programming languages like R, Python, and hands on experience database query languages like SQL.

• Proficiency in essential Python libraries - NumPy, pandas, scikit-learn, TensorFlow/PyTorch, seaborn, and BeautifulSoup/Scrapy for web scraping when necessary.

• Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc.

• Basic Math Skills (Linear Algebra) - understanding the fundamentals of Linear Algebra.

• Knowledge with Timeseries data analysis and modelling.

• Knowledge with regular expressions.

• Knowledge with Data Visualization Tools like Power BI, Spotfire, Tableau, matplotlib, etc.

• Great numerical and analytical skills

• Excellent Communication Skills –efficiently communicating with both a technical and non-technical audience.