Digital – Software Engineer III (Data Mining Engineer)

FactSet

India, Hyderabad, DVS, SEZ-1 – Orion B4; FL 7, 8, 9, 11 (Hyderabad - Divyasree 3)

5d ago

VALUES THAT DEFINE OUR CULTURE

We are unified by the spirit of going above and beyond for our clients and each other. We look to foster a globally inclusive culture, enabling our people to be themselves at work and to join in, be heard, contribute, and grow.

We continually seek to expand our workforce with diverse perspectives, backgrounds, and experiences. We recognize that our best ideas can come from anyone, anywhere, at any time and help us provide the best solutions for our clients around the globe.

Our inclusive work environment maximizes our diversity values, engagement, productivity, and ultimately makes FactSet a fun place to work.

JOB RESPONSIBILITIES

Data Mining engineer, knowledge on basic statistics and a good and enthusiastic learner.

FactSet Data Science team is currently seeking Data scientist or Data Mining Engineer’s to join our Data Lake team.

As part of this team, one would work on individual projects where he / she will be responsible for its end to end development, presenting results and Integration and deployment as well.

His or her work would include Exploring and analysing historical Data and raw Data with data mining techniques and working on providing solutions for Automation with a wide variety of sources of data, working with other Data Lake team members and collaborating in building the Data Lake and enhancing Data and providing Insights for the Lake and building Api’s, constantly enhancing the API capabilities and solving complex problems.

JOB REQUIREMENTS : Must have

Computer skills

Practice of programming in Python

Comfortable working in Linux and windows environment

Practice of source control, code review, testing frameworks

Practice of Big Data frameworks, like Hadoop, Spark

Knowledge of both Sql and noSql databases (Columns, Documents, Key-Value)

Cloud

Basic knowledge of cloud environment, constraints and opportunities

Statistics

Basic statistics knowledge, probability, correlation, regression, linear algebra, stochastic process

Practice of data analysis, data cleanup, data investigation, how to detect and handle unbalance, bias and noise

Proficient in data structures and algorithms, in particular : lists, queues, trees, graphs, and sorting, searching, traversing, dynamic programming, and map-reduce pattern

Knowledge and practice of Machine Learning and NN algorithms and frameworks

Knowledge and practice of Natural Language Processing

Others

Practice of data mining and data science projects, from understanding the problem to presenting results and deploying in production

Communication skills, project presentation, capacity to popularize technics and results

Knowledge of Data Mining / Data Science projects and publications

Computer skills

Practice of programming in other languages like R, java, Julia, Matlab

Practice working on Jupyter notebook / lab or VS Code

Practice working on Git / Github

Cloud

Practice on AWS cloud / SageMaker

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