Aggregate Intelligence - Data Science Engineer - Python Programming (5-10 yrs)

Primary Responsibilities :

Work closely with project managers and product heads to understand data needs and determine how data can be effectively worked on to achieve those goals. The ideal Data Science Engineer is responsible for designing data modelling processes, creating algorithms and predictive models to enable data extraction per business needs, analysis of data and presentation of trends and other valuable insights.

Job Summary :

- Assess the effectiveness of data sources and data-gathering techniques and improve data

- collection methods; Perform data analysis and statistical tasks using Python.

- Develop and maintain APIs with frameworks such as Flask or FastAPI

- Test and maintain APIs to ensure reliability and performance

- Pipeline Design / Maintenance and Orchestration

- Ability to mine and analyze data sets and develop custom data models for effective data processing, cleansing and verification at all stages in the data cycle

- Analyze large amounts of information to discover trends and patterns; Generate reports using Python libraries like pandas and xlsxwriter.

- Build predictive models and machine-learning algorithms

- Use machine learning tools and statistical techniques such as statistical modelling, and

- artificial intelligence to produce solutions to problems; Test data mining models to select the most appropriate ones for use on a project

- Develop processes and tools to monitor and analyze model performance and data accuracy

- Present information using data visualization tools or other methods

Qualification Criteria and other Skills:

- Demonstrated experience applying data science methods to real-world data problems

- Experience using statistical computer languages to manipulate data and draw insights from large data sets

- Proficiency in Python, including libraries such as pandas and numpy; Expert in SQL and relational databases; R is an added advantage

- Knowledge in Spark / PySpark, Airflow, Tensorflow, Keras, PyTorch and Kafka

- Experience with Flask or FastAPI for API development.

- Familiarity with API testing and maintenance, and exposure to cloud platforms

- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and understanding of their real-world advantages / drawbacks; experience in applying these techniques and importantly creating algorithms in real time is a requisite

- Hands-on experience in application of ML models is a must

- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications

- Excellent communication, Analytical, Statistical and presentation skills

- Experience on business intelligence tools (Power BI, Tableau) and data frameworks (like Hadoop) is an added advantage

- Problem solving and Critical thinking ability; Independent and highly motivated individual; excellent communicator