Location: Chennai
Experience: 2+ Years
Skill: Knowledge for Data Scientist
Required skills:
- Master’s degree in Software Engineering or related field
- Machine learning techniques in high-dimensional spaces including linear models, kernels, ensembles, regularization, dimensionality reduction, data mining, and clustering
- Hands-on experience in Hadoop or Big Data querying
- Strong programming skills using R, SQL, and Python
- Familiarity with Scala, Java, or C++
- Knowledge of RDBMS concepts and experience working with SQL
- Implementation knowledge on linear regression, Bayesian, Decision forest, K-Means, one-class SVM, Multiclass regression algorithms (predictive analytics)
- Experience working on Prediction/Prescriptive analytics/Forecasting algorithm
- Implementation experience of different Classification, Regression, Predictive, Anomaly detection algorithms
- 2-4+ years of experience in Hadoop Ecosystem fluency (MapReduce, HBase, Kafka, etc.) and/or Apache Spark/PySpark 1.5+
- Implementation knowledge of REST API and JSON for data exchange
- Ability to deliver products in a timely manner with high quality
- Familiarity with multiple software development practices and tools and the proven ability to adapt, champion, and institute good practices and tools
- Ability to write and execute complex queries in SQL
- Hands-on experience in Machine learning techniques such as supervised machine learning, decision trees, logistic regression, etc.
- Ability to visualize data with the aid of data visualization tools such as ggplot, d3.js, and Matplottlib, and Tableau
- Self-motivated and self-directed abilities to prioritize and execute tasks in a high-pressure environment with time critical deadlines
Preferred skills:
- Specialization in social sciences, physical sciences, or statistics
- Knowledge of Agile Scrum methodology
- Experience designing and solving Data Science related to real-world problems related to the education sector
- Experience with Hive or Pig
- Advanced machine learning skills such as Supervised machine learning, Unsupervised machine learning, Time series, natural language processing, Outlier detection, Computer vision, Recommendation engines, Survival analysis, Reinforcement learning, and Adversarial learning