Data Scientist - Bangalore Metropolitan Area, India - mPokket

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 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