Data Scientist

• 6+ years Experienced in building data pipelines and deployment pipelines for machine learning models
• 4+ years’ experience with ML/AI toolkits such as Tensorflow, Keras, AWS Sagemaker, MXNet, H20, etc.
• 4+ years’ experience developing ML/AI models in Python/R
• Must have leadership abilities to lead a project and team.
• Must have leadership skills to lead and deliver projects, be proactive, take ownership, interface with business, represent the team and spread the knowledge.
• Strong knowledge of statistical data analysis and machine learning techniques (e.g., Bayesian, regression, classification, clustering, time series, deep learning).
• Should be able to help deploy various models and tune them for better performance.
• Working knowledge in operationalizing models in production using model repositories, API s and data pipelines.
• Experience with machine learning and computational statistics packages.
• Experience with Data Bricks, Data Lake.
• Experience with Dremio, Tableau, Power Bi.
• Experience working with spark ML, spark DL with Pyspark would be a big plus!
• Working knowledge of relational database systems like SQL Server, Oracle.
• Knowledge of deploying models in platforms like PCF, AWS, Kubernetes.
• Good knowledge in Continuous integration suites like Jenkins.
• Good knowledge in web servers (Apache, NGINX).
• Good knowledge in Git, Github, Bitbucket.
• Working knowledge in operationalizing models in production using model repositories, APIs and data pipelines.
• Java, R, and Python programming experience.
• Should be very familiar with (MS SQL, Teradata, Oracle, DB2).
• Big Data – Hadoop.
• Expert knowledge using BI tools e.g.Tableau
• Experience with machine learning and computational statistics packages.

Daily and monthly responsibilities

• Review and coordinate with business application teams on data delivery requirements.
• Develop estimation and proposed delivery schedules in coordination with development team.
• Develop sourcing and data delivery designs.
• Review data model, metadata and delivery criteria for solution.
• Review and coordinate with team on test criteria and performance of testing.
• Contribute to the design, development and completion of project deliverables.
• Complete in-depth data analysis and contribution to strategic efforts
• Complete understanding of how we manage data with focus on improvement of how data is sourced and managed across multiple business areas.

Basic Qualifications

• Bachelor’s degree.
• 5+ years of data analysis working with business data initiatives.
• Knowledge of Structured Query Language (SQL) and use in data access and analysis.
• Proficient in data management including data analytical capability.
• Excellent verbal and written communications also high attention to detail.
• Experience with Python.
• Presentation skills in demonstrating system design and data analysis solutions.

1. Big data developer with 8+ years of professional IT experience with expertise in Hadoop ecosystem components in ingestion, Data modeling, querying, processing, storage, analysis, Data Integration and Implementing enterprise level systems spanning Big Data.
2. A skilled developer with strong problem solving, debugging and analytical capabilities, who actively engages in understanding customer requirements.
3. Expertise in Apache Hadoop ecosystem components like Spark, Hadoop Distributed File Systems(HDFS), HiveMapReduce, Hive, Sqoop, HBase, Zookeeper, YARN, Flume, Pig, Nifi, Scala and Oozie.
4. Hands on experience in creating real - time data streaming solutions using Apache Spark core, Spark SQL & DataFrames, Kafka, Spark streaming and Apache Storm.
5. Excellent knowledge of Hadoop architecture and daemons of Hadoop clusters, which include Name node,Data node, Resource manager, Node Manager and Job history server.
6. Worked on both Cloudera and Horton works in Hadoop Distributions. Experience in managing Hadoop clustersusing Cloudera Manager tool.
7. Well versed in installation, Configuration, Managing of Big Data and underlying infrastructure of Hadoop Cluster.
8. Hands on experience in coding MapReduce/Yarn Programs using Java, Scala and Python for analyzing Big Data.
9. Exposure to Cloudera development environment and management using Cloudera Manager.
10. Extensively worked on Spark using Scala on cluster for computational (analytics), installed it on top of Hadoop performed advanced analytical application by making use of Spark with Hive and SQL/Oracle .
11. Implemented Spark using PYTHON and utilizing Data frames and Spark SQL API for faster processing of data and handled importing data from different data sources into HDFS using Sqoop and performing transformations using Hive, MapReduce and then loading data into HDFS.
12. Used Spark Data Frames API over Cloudera platform to perform analytics on Hive data.
13. Hands on experience in MLlib from Spark which are used for predictive intelligence, customer segmentation and for smooth maintenance in Spark streaming.
14. Experience in using Flume to load log files into HDFS and Oozie for workflow design and scheduling.
15. Experience in optimizing MapReduce jobs to use HDFS efficiently by using various compression mechanisms.
16. Working on creating data pipeline for different events of ingestion, aggregation, and load consumer response data into Hive external tables in HDFS location to serve as feed for tableau dashboards.
17. Hands on experience in using Sqoop to import data into HDFS from RDBMS and vice-versa.
18. In-depth Understanding of Oozie to schedule all Hive/Sqoop/HBase jobs.
19. Hands on expertise in real time analytics with Apache Spark.
20. Experience in converting Hive/SQL queries into RDD transformations using Apache Spark, Scala and Python.
21. Extensive experience in working with different ETL tool environments like SSIS, Informatica and reporting tool environments like SQL Server Reporting Services (SSRS).
22. Experience in Microsoft cloud and setting cluster in Amazon EC2 & S3 including the automation of setting & extending the clusters in AWS Amazon cloud.
23. Extensively worked on Spark using Python on cluster for computational (analytics), installed it on top of Hadoop performed advanced analytical application by making use of Spark with Hive and SQL.
24. Strong experience and knowledge of real time data analytics using Spark Streaming, Kafka and Flume.
25. Knowledge in installation, configuration, supporting and managing Hadoop Clusters using Apache, Cloudera (CDH3, CDH4) distributions and on Amazon web services (AWS).
26. Experienced in writing Ad Hoc queries using Cloudera Impala, also used Impala analytical functions.
27. Experience in creating Data frames using PySpark and performing operation on the Data frames using Python.
28. In depth understanding/knowledge of Hadoop Architecture and various components such as HDFS and MapReduce Programming Paradigm, High Availability and YARN architecture.
29. Establishing multiple connections to different Redshift clusters (Bank Prod, Card Prod, SBBDA Cluster) and provide the access for pulling the information we need for analysis. 
30. Generated various kinds of knowledge reports using Power BI based on Business specification. 
31. Developed interactive Tableau dashboards to provide a clear understanding of industry specific KPIs using quick filters and parameters to handle them more efficiently.
32. Well Experience in projects using JIRA, Testing, Maven and Jenkins build tools.
33. Experienced in designing, built, and deploying and utilizing almost all the AWS stack (Including EC2, S3,), focusing on high-availability, fault tolerance, and auto-scaling.
34. Good experience with use-case development, with Software methodologies like Agile and Waterfall.
35. Working knowledge of Amazon's Elastic Cloud Compute( EC2 ) infrastructure for computational tasks and Simple Storage Service ( S3 ) as Storage mechanism.
36. Good working experience in importing data using Sqoop, SFTP from various sources like RDMS, Teradata, Mainframes, Oracle, Netezza to HDFS and performed transformations on it using Hive, Pig and Spark .
37. Extensive experience in Text Analytics, developing different Statistical Machine Learning solutions to various business problems and generating data visualizations using Python and R.
38. Proficient in NoSQL databases including HBase, Cassandra, MongoDB and its integration with Hadoop cluster.
39. Hands on experience in Hadoop Big data technology working on MapReduce, Pig, Hive as Analysis tool, Sqoop and Flume data import/export tools.

Technical & Business Expertise:

-Hands on integration experience in SSIS/Mulesoft
- Hands on experience Azure Synapse
- Proven advanced level of writing database experience in SQL Server
- Proven advanced level of understanding about Data Lake
- Proven intermediate level of writing Python or similar programming language
- Intermediate understanding of Cloud Platforms (GCP) 
- Intermediate understanding of Data Warehousing
- Advanced Understanding of Source Control (Github)

Role : 

• Understand and translate statistics and analytics to address business problems
• Responsible for helping in data preparation and data pull, which is the first step in machine learning
• Should be able to do cut and slice data to extract interesting insights from the data
• Model development for better customer engagement and retention
• Hands on experience in relevant tools like SQL(expert), Excel, R/Python
• Working on strategy development to increase business revenue

Requirements:

• Hands on experience in relevant tools like SQL(expert), Excel, R/Python
• Statistics: Strong knowledge of statistics
• Should able to do data scraping & Data mining
• Be self-driven, and show ability to deliver on ambiguous projects
• An ability and interest in working in a fast-paced, ambiguous and rapidly-changing environment
• Should have worked on Business Projects for an organization, Ex: customer acquisition, Customer retention.

• Design, create, test, and maintain data pipeline architecture in collaboration with the Data Architect.
• Build the infrastructure required for extraction, transformation, and loading of data from a wide variety of data sources using Java, SQL, and Big Data technologies.
• Support the translation of data needs into technical system requirements. Support in building complex queries required by the product teams.
• Build data pipelines that clean, transform, and aggregate data from disparate sources
• Develop, maintain and optimize ETLs to increase data accuracy, data stability, data availability, and pipeline performance.
• Engage with Product Management and Business to deploy and monitor products/services on cloud platforms.
• Stay up-to-date with advances in data persistence and big data technologies and run pilots to design the data architecture to scale with the increased data sets of consumer experience.
• Handle data integration, consolidation, and reconciliation activities for digital consumer / medical products.

Job Qualifications:

• Bachelor’s or master's degree in Computer Science, Information management, Statistics or related field
• 5+ years of experience in the Consumer or Healthcare industry in an analytical role with a focus on building on data pipelines, querying data, analyzing, and clearly presenting analyses to members of the data science team.
• Technical expertise with data models, data mining.
• Hands-on Knowledge of programming languages in Java, Python, R, and Scala.
• Strong knowledge in Big data tools like the snowflake, AWS Redshift, Hadoop, map-reduce, etc.
• Having knowledge in tools like AWS Glue, S3, AWS EMR, Streaming data pipelines, Kafka/Kinesis is desirable.
• Hands-on knowledge in SQL and No-SQL database design.
• Having knowledge in CI/CD for the building and hosting of the solutions.
• Having AWS certification is an added advantage.
• Having Strong knowledge in visualization tools like Tableau, QlikView is an added advantage
• A team player capable of working and integrating across cross-functional teams for implementing project requirements. Experience in technical requirements gathering and documentation.
• Ability to work effectively and independently in a fast-paced agile environment with tight deadlines
• A flexible, pragmatic, and collaborative team player with the innate ability to engage with data architects, analysts, and scientists

We are building a global content marketplace that brings companies and content

creators together to scale up content creation processes across 50+ content verticals and 150+ industries. Over the past 2.5 years, we’ve worked with companies like India Today, Amazon India, Adobe, Swiggy, Dunzo, Businessworld, Paisabazaar, IndiGo Airlines, Apollo Hospitals, Infoedge, Times Group, Digit, BookMyShow, UpGrad, Yulu, YourStory, and 350+ other brands.
Our mission is to become the world’s largest content creation and distribution platform for all kinds of content creators and brands.

Our Team

We are a 25+ member company and is scaling up rapidly in both team size and our ambition.

If we were to define the kind of people and the culture we have, it would be -

a) Individuals with an Extreme Sense of Passion About Work

b) Individuals with Strong Customer and Creator Obsession

c) Individuals with Extraordinary Hustle, Perseverance & Ambition

We are on the lookout for individuals who are always open to going the extra mile and thrive in a fast-paced environment. We are strong believers in building a great, enduring

a company that can outlast its builders and create a massive impact on the lives of our

employees, creators, and customers alike.

Our Investors

We are fortunate to be backed by some of the industry’s most prolific angel investors - Kunal Bahl and Rohit Bansal (Snapdeal founders), YourStory Media. (Shradha Sharma); Dr. Saurabh Srivastava, Co-founder of IAN and NASSCOM; Slideshare co-founder Amit Ranjan; Indifi's Co-founder and CEO Alok Mittal; Sidharth Rao, Chairman of Dentsu Webchutney; Ritesh Malik, Co-founder and CEO of Innov8; Sanjay Tripathy, former CMO, HDFC Life, and CEO of Agilio Labs; Manan Maheshwari, Co-founder of WYSH; and Hemanshu Jain, Co-founder of Diabeto.
Backed by Lightspeed Venture Partners

High Level Scope of Work :

• Work with AI / Analytics team to priorities MACHINE LEARNING Identified USE CASES for Development and Rollout
• Meet and understand current retail / Marketing Requirements and how AI/ML solution will address and automate the decision process.
• Develop AI/ML Programs using DATAIKU Solution & Python or open source tech with focus to deliver high Quality and accurate ML prediction Model
• Gather additional and external data sources to support the AI/ML Model as desired .
• Support the ML Model and FINE TUNEit to ensure high accuracy all the time.
• Example of use cases (Customer Segmentation , Product Recommendation, Price Optimization, Retail Customer Personalization Offers, Next Best Location for Business Est, CCTV Computer Vision, NLP and Voice Recognition Solutions)

Required technology expertise :

• Deep Knowledge & Understanding on MACHINE LEARNING ALGORITHMS (Supervised / Unsupervised Learning / Deep Learning Models)
• Hands on EXP for at least 5+ years with PYTHON and R STATISTICS PROGRAMMING Languages
• Strong Database Development knowledge using SQL and PL/SQL
• Must have EXP using Commercial Data Science Solution particularly DATAIKU and (Altryx, SAS, Azure ML, Google ML, Oracle ML is a plus)
• Strong hands on EXP with BIG DATA Solution Architecture and Optimization for AI/ML Workload.
• Data Analytics and BI Tools Hand on EXP particularly (Oracle OBIEE and Power BI)
• Have implemented and Developed at least 3 successful AI/ML Projects with tangible Business Outcomes In retail Focused Industry
• Have at least 5+ Years EXP in Retail Industry and Customer Focus Business.
• Ability to communicate with Business Owner & stakeholders to understand their current issues and provide MACHINE LEARNING Solution accordingly.

Qualifications

• Bachelor Degree or Master Degree in Data Science, Artificial Intelligent, Computer Science
• Certified as DATA SCIENTIST or MACHINE LEARNING Expert.