AM - Data Science

Job Description

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 youre also able to align our data products with our business goals, wed 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 companys 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 3+ 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