Data Scientist

We are looking to hire a highly creative Data Scientist to address data analytics challenges in our organization, to collect large volumes of data from varying sources, clean and interpret data, create solutions to overcome challenges and communicate with interested parties.

To succeed in this position; you need to be curious, creative and tech savvy. You need to stay up to date with data programming software and apps, have outstanding understanding of statistics and mathematics, and be proficient in writing algorithms. Top candidates will be persistent, and have excellent analytical and problem-solving skills.

Responsibilities:

1. Having meetings with team members regarding projects.
2. Collecting, Processing, Cleansing and verifying the integrity of data for further analysis
3. Automating and integrating processes.
4. Researching solutions to overcome data analytics challenges.
5. Developing complex mathematical models that integrate business rules and requirements.
6. Creating machine learning models.
7. Communicating and meeting with engineers, IT teams and other interested parties.
8. Sharing complex ideas verbally and visually in an understandable manner with non-technical stakeholders.

Requirements:

1. BS/MS in Computer Science/Applied Mathematics/Data Science or Statistics.
2. 3 to 5 years industry experience.
3. Experience with collecting and integrating data from multiple sources (Databases, Data warehouses, Web, Api, Text, Images).
4. Fluency in Python stack for data processing, visualization and modelling (Numpy, Pandas, Matplotlib, Seaborn, Sk-learn, Keras, Tensorflow)
5.  Strong understanding of statistical techniques (regression, properties of distributions, correlation, statistical tests - ARIMA, ANOVA and their proper usage, etc.) and machine learning concepts (classification, clustering, decision tree learning, ensembles, artificial neural networks, etc.).
6. Experience working with huge data sets and distributed computing tools (Hadoop, Map/Reduce, Spark) distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, etc.
7. Experience using data Tableau, PowerBI, Data Studio, Plotly etc
8. Strong understanding of databases and proficiency in SQL
9. Experience with any deep learning framework (Keras, Pytorch, Tensorflow, Theano) is a plus.
10. Experience with data analytics and machine learning services offered by cloud vendors - AWS, GCP.