Job Description :
Role: Solution Architect Spark/Python
Location: Los Angeles,CA
Duration: 1 month
Responsibilities :
Understand the current landscape of customer and identify potential scope for data science area Ideate and implement analytical models for customer ,Mine the data and provide more business insights to customer by building various models .
Required Experience :
PhD or MS in Statistics, Computer Science, Machine Learning, Operations Research, Econometrics or related field.
5 years of experience in the Data Analytics space with a proven track of record of delivering business value through data insights and developing data products.
Experience in the media industry or advertising industry, specially in the fields of consumer analytics, social media analytics and campaign optimization.
Exceptional communication skills and experience with data story telling.
Ability to define and test hypotheses that will provide business insights in a quantifiable, repeatable and consistent way using experimentation and statistical methods.
Ability to collaborate with different business units to identify opportunities for advanced data analytics to drive business value and define a plan to achieve and measure the results with statistical rigor.
Experience building Machine Learning models for classification and regression problems and evaluating its performance. Knowledge about advanced AI techniques in the field of Natural Language Processing and chatbot technologies. Ability to identify business KPIs and build data visualization and executive dashboards.
Experience with scripting and analytical languages such as Python, Scala, and Java. Fluency in SQL and non-SQL related technologies Redshift, Hive, DynamoDB, Hbase for both structured and non-structured data analysis.
Experience with document based storage technologies such as ElasticSearch or MongoDB.
Experience creating data wrangling and transformation pipelines using Spark. Experience with scalable machine learning libraries such as MLlib, H2O, Mahout, etc.
Familiarity with Deep Learning frameworks such as Tensorflow, Keras, Theano, etc.
Familiarity with Data Analytics packages such as Pandas, Scikit-learn, Numpy or R.
Familiarity with Data Visualization libraries and tools such as Tableau, D3.js, matplotlib, ggplot, etc.