Data Scientist

• At least 4 to 7 years of relevant experience as Big Data Engineer
• Hands-on experience in Scala or Python
• Hands-on experience on major components in Hadoop Ecosystem like HDFS, Map Reduce, Hive, Impala.
• Strong programming experience in building applications/platform using Scala or Python.
• Experienced in implementing Spark RDD Transformations, actions to implement business analysis

• Partnering with internal business owners (product, marketing, edit, etc.) to understand needs and develop custom analysis to optimize for user engagement and retention
• Good understanding of the underlying business and workings of cross functional teams for successful execution
• Design and develop analyses based on business requirement needs and challenges.
• Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, etc.
• Providing statistical analysis on custom research projects and consult on A/B testing and other statistical analysis as needed. Other reports and custom analysis as required.
• Identify and use appropriate investigative and analytical technologies to interpret and verify results.
• Apply and learn a wide variety of tools and languages to achieve results
• Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.

• 2 - 4 years  of relevant experience in Data science.
• Preferred education: Bachelor's degree in a technical field or equivalent experience.
• Experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.
• Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, XGBoost, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, boosting and ensemble methods.
• Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open source tools.
• Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query and analysis.
• Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts.
• Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE).
• Experience in risk and credit score domains preferred.

• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:

• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.

• Strong in problem solving, algorithms and data structures
• Proficient in Python
• Hands on experience in technologies and tools related to any of NLP, Deep learning, Machine learning, Conversational AI
• Experience with knowledge Graph or any graph based system is plus
• Able to train and deploy models
• Broad knowledge of machine learning algorithms and principles
• Performance profiling and Tuning
• Communicate and propose solutions to business challenges
• Familiarity with at least one of the cloud computing infrastructure - GCP/AWS
• Keep abreast with the latest technological advances
• Team mentoring and leadership skills.

Responsibilities: 

• Identify complex business problems and work towards building analytical solutions in-order to create large business impact.
• Demonstrate leadership through innovation in software and data products from ideation/conception through design, development and ongoing enhancement, leveraging user research techniques, traditional data tools, and techniques from the data science toolkit such as predictive modelling, NLP, statistical analysis, vector space modelling, machine learning etc.
• Collaborate and ideate with cross-functional teams to identify strategic questions for the business that can be solved and champion the effectiveness of utilizing data, analytics, and insights to shape business.
• Contribute to company growth efforts, increasing revenue and supporting other key business outcomes using analytics techniques.
• Focus on driving operational efficiencies by use of data and analytics to impact cost and employee efficiency.
• Baseline current analytics capability, ensure optimum utilization and continued advancement to stay abridge with industry developments.
• Establish self as a strategic partner with stakeholders, focused on full innovation system and fully supportive of initiatives from early stages to activation.
• Review stakeholder objectives and team's recommendations to ensure alignment and understanding.
• Drive analytics thought leadership and effectively contributes towards transformational initiatives.
• Ensure accuracy of data and deliverables of reporting employees with comprehensive policies and processes.