Job Location: Bengaluru
Working closely with the technology and learning teams, the Data Scientist will be responsible for the following:
- Creating infrastructure for the delivery team; Maintain a working knowledge of data mining and visualization best practices; Work in coordination with the team for better and quick results;
- Being able to develop or program databases; Having the ability to query databases and perform statistical analysis; Analyze the data available and provide the relevant output;
- Collaborate with engineering colleagues to define the data modeling goals for designated project areas;
- Having a good understanding of design and architecture principles; Understand the importance of the system development and help in getting it implemented;
Have good time management skills and should be able to meet the expected deliverables;
Being able to create examples, prototypes, demonstrations to help management better understand the work;
Capacity to motivate and train junior scientists and offer counsel to peers. Being able to work autonomously; -
Basic Qualifications:
Passion, commitment, resourcefulness, and a drive to continue learning are essential prerequisites. For this role, we re also looking for someone who meets the following criteria:
- PhD Master s Degree in Statistics, Mathematics, Computer Science, or equivalent; 5+ years of data science mining experience;
- Excellent knowledge of at least two coding languages, e.g. Python, Java, Scala, R Language, SQL, ETL Tools, Perl and Pig;
- Should have worked on different tools like Java, SQL, Python, etc.; Good experience with SQL, Linux shell scripts, Perl, and AWK;
- Domain knowledge in at least two industries; Minimum five years of experience in customer-facing activities;
- Overall knowledge of Business Intelligence; in particular, data modeling, ETL, and reporting tools;
- Extensive hands on experience working with very large data sets, including statistical analyses, data visualization, data mining, and data cleansingtransformation;
- Under-the-hood knowledge of many of these machine learning concepts: supervisedunsupervised learning, loss functions, regularization, feature selection, regressionclassification, cross-validation, bagging, kernel methods, sampling, probability distributions;
- Experience prototyping and developing data mining solutions using statistical software packages (R, H2O);
- Excellent verbal and written communication; Good analytical and interpersonal skills;
- Strong ability to communicate deep analytical results in forms that resonate with scientific andor business collaborators, highlighting actionable insights;
Entrepreneurial inclination to discover novel opportunities for applying analytical techniques to businessscientific problems across the company. -
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