A data scientist is expected to:
- Develop and deploy machine learning models and evaluate their performance
- Generate descriptive analytics and visualize data in ways to provide insights
- Investigate issues with either the quantitative output or the logical delivery (i.e., systems issues) for different models
- Demonstrate skills working with teams to deliver data science driven solutions
Bachelor or Masters in Engineering / Science / Mathematics / Economics / Physics or an equivalent degree from an institution of repute.
1 to 4 years of relevant experience in building data science solutions for solving business problems
- Relate to business problems and understand business data
- Demonstrate strong skills in data preprocessing and data wrangling
- Process, cleanse and verify the integrity of data used for analysis
- Be capable to analyze high volume of data and derive insights, correlations
- Enhance data collection procedures to include information that is relevant to building analytic systems
- Implement statistical and machine learning models and evaluate the outcome
- Visualize data and present insights to business
- Work in iterative processes with the client or team and validate findings
- Collaborate with engineering and product development teams
- Perform ad-hoc analysis and present results in a coherent manner
- Create automated anomaly detection systems and constant tracking of its performance
- Follow agile practices and complete the tasks allocated as planned
- Be adept in timely communication on work progress
- Good understanding of machine learning techniques and algorithms such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Experience with common data science toolkits such as R, Weka, NumPy, MatLab, etc. Excellence in at least one of these is highly desirable
- Experience with data visualization tools, such as D3.js, GGplot, etc.
- Experience in practical data science solutions delivery
- Experience in programming languages like C/C++/Java/Python.
- Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms
Desirable to have
- Familiarity with batch processing technologies like Spark, MapReduce and Pig
- Familiarity with SQL technologies like Hive, Drill and Impala
- Familiarity with OLAP NoSQL databases like HBase, Neo4J and MongoDB
- Familiarity with enterprise big data distribution platforms like Cloudera, Hortonworks and MapR
- Knowledge and experience in Scrum framework/ Agile methodology
- Provable excellence in past record, problem solving and analytical skills, a penchant to excel, a strong urge to learn, interpersonal skills to work with and an inclusive attitude to respect diverse individuals and perspectives
Quadratyx is an equal opportunity employer - we will never differentiate candidates on the basis of religion, caste, gender, language, disabilities or ethnic group.
Quadratyx reserves the right to place/move any candidate to any company location, partner location or customer location globally, in the best interest of Quadratyx business.
Interested candidate profiles should be emailed firstname.lastname@example.org