Data Scientist
1 month ago
We are looking for a Data Scientist to help us gain useful insight out of raw data.
Data Scientist responsibilities include working with the data science team, planning projects and building analytics models. You should have a strong problem-solving ability and a knack for statistical analysis. If you’re also able to align our data products with our business goals, we’d like to meet you. Your ultimate goal will be to help improve our products and business decisions by making the most out of our data.
Key Responsibilities
Responsible for overseeing the data scientists team and data specialists
Teach, lead, and counsel colleagues on new techniques or solutions
Collaborate with data and software engineers to enable deployment of sciences and technologies that will scale across the company’s ecosystem
Responsible for the conception, planning, and prioritizing of data projects
Responsible for building analytic systems and predictive models as well as experimenting with new models and techniques
Ensure that data projects align with organizational goals
Minimum Qualification
Master's degree in Computer Science, Operations Research, Econometrics, Statistics or related technical field
5+ years of experience solving analytical problems using quantitative approaches
Experience communicating quantitative analysis results
Knowledge with relational databases and SQL
Development experience in any scripting language (PHP, Python, Perl, etc.)
Knowledge of statistics (e.g., hypothesis testing, regressions)
Experience manipulating data sets through statistical software (ex. R, SAS) or other methods
Technical Skills -
Must have –
Programming – Python (Preferred) / R
ML Models – i. Regression – Linear, Logistic, Multinomial, Mixed effect
Classification – Bagging & Boosting (Random Forest), Decision tree, SVM
Clustering – K-Means, hierarchical, DB-Scan
Time series – ARIMA, SARIMA, ARIMAX, Holt-Winters, Multi TS (VAR), UCM
Neural Networks (Deep learning), Naive Bayes
Excel and SQL
Dimensionality Reduction – PCA, SVD etc.
Optimization Techniques – Linear programming, Gradient Descent, Genetic Algorithm
Cloud – Understanding of Azure / AWS offerings, Setting up ML pipeline of cloud
Good to have –
Visualization – Tableau / Power BI / Looker / QlikView
Data management – HDFS, Spark, Advanced Excel
Agile Tools – Azure DevOps, JIRA
Pyspark
Big Data/Hive Database
IDE: Pycharm
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