11+ Data steward Jobs in Bangalore (Bengaluru) | Data steward Job openings in Bangalore (Bengaluru)

1. Data Steward :

Data Steward will collaborate and work closely within the group software engineering and business division. Data Steward has overall accountability for the group's / Divisions overall data and reporting posture by responsibly managing data assets, data lineage, and data access, supporting sound data analysis. This role requires focus on data strategy, execution, and support for projects, programs, application enhancements, and production data fixes. Makes well-thought-out decisions on complex or ambiguous data issues and establishes the data stewardship and information management strategy and direction for the group. Effectively communicates to individuals at various levels of the technical and business communities. This individual will become part of the corporate Data Quality and Data management/entity resolution team supporting various systems across the board.

Primary Responsibilities:

• Responsible for data quality and data accuracy across all group/division delivery initiatives.
• Responsible for data analysis, data profiling, data modeling, and data mapping capabilities.
• Responsible for reviewing and governing data queries and DML.
• Accountable for the assessment, delivery, quality, accuracy, and tracking of any production data fixes.
• Accountable for the performance, quality, and alignment to requirements for all data query design and development.
• Responsible for defining standards and best practices for data analysis, modeling, and queries.
• Responsible for understanding end-to-end data flows and identifying data dependencies in support of delivery, release, and change management.
• Responsible for the development and maintenance of an enterprise data dictionary that is aligned to data assets and the business glossary for the group responsible for the definition and maintenance of the group's data landscape including overlays with the technology landscape, end-to-end data flow/transformations, and data lineage.
• Responsible for rationalizing the group's reporting posture through the definition and maintenance of a reporting strategy and roadmap.
• Partners with the data governance team to ensure data solutions adhere to the organization’s data principles and guidelines.
• Owns group's data assets including reports, data warehouse, etc.
• Understand customer business use cases and be able to translate them to technical specifications and vision on how to implement a solution.
• Accountable for defining the performance tuning needs for all group data assets and managing the implementation of those requirements within the context of group initiatives as well as steady-state production.
• Partners with others in test data management and masking strategies and the creation of a reusable test data repository.
• Responsible for solving data-related issues and communicating resolutions with other solution domains.
• Actively and consistently support all efforts to simplify and enhance the Clinical Trial Predication use cases.
• Apply knowledge in analytic and statistical algorithms to help customers explore methods to improve their business.
• Contribute toward analytical research projects through all stages including concept formulation, determination of appropriate statistical methodology, data manipulation, research evaluation, and final research report.
• Visualize and report data findings creatively in a variety of visual formats that appropriately provide insight to the stakeholders.
• Achieve defined project goals within customer deadlines; proactively communicate status and escalate issues as needed.

Additional Responsibilities:

• Strong understanding of the Software Development Life Cycle (SDLC) with Agile Methodologies
• Knowledge and understanding of industry-standard/best practices requirements gathering methodologies.
• Knowledge and understanding of Information Technology systems and software development.
• Experience with data modeling and test data management tools.
• Experience in the data integration project • Good problem solving & decision-making skills.
• Good communication skills within the team, site, and with the customer

Knowledge, Skills and Abilities

• Technical expertise in data architecture principles and design aspects of various DBMS and reporting concepts.
• Solid understanding of key DBMS platforms like SQL Server, Azure SQL
• Results-oriented, diligent, and works with a sense of urgency. Assertive, responsible for his/her own work (self-directed), have a strong affinity for defining work in deliverables, and be willing to commit to deadlines.
• Experience in MDM tools like MS DQ, SAS DM Studio, Tamr, Profisee, Reltio etc.
• Experience in Report and Dashboard development
• Statistical and Machine Learning models
• Python (sklearn, numpy, pandas, genism)
• Nice to Have:
• 1yr of ETL experience
• Natural Language Processing
• Neural networks and Deep learning
• xperience in keras,tensorflow,spacy, nltk, LightGBM python library

Interaction :  Frequently interacts with subordinate supervisors.

Education : Bachelor’s degree, preferably in Computer Science, B.E or other quantitative field related to the area of assignment. Professional certification related to the area of assignment may be required

Experience :  7 years of Pharmaceutical /Biotech/life sciences experience, 5 years of Clinical Trials experience and knowledge, Excellent Documentation, Communication, and Presentation Skills including PowerPoint

Responsibilities

• Work with large and complex blockchain data sets and derive investment relevant metrics in close partnership with financial analysts and blockchain engineers.
• Apply knowledge of statistics, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to the development of fundamental metrics needed to evaluate various crypto assets.
• Build a strong understanding of existing metrics used to value various decentralized applications and protocols.
• Build customer facing metrics and dashboards.
• Work closely with analysts, engineers, Product Managers and provide feedback as we develop our data analytics and research platform.

Qualifications

• Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience (or) degree in an analytical field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research, Management Science)
• 3+ years experience with data analysis and metrics development
• 3+ years experience analyzing and interpreting data, drawing conclusions, defining recommended actions, and reporting results across stakeholders
• 2+ years experience writing SQL queries
• 2+ years experience scripting in Python
• Demonstrated curiosity in and excitement for Web3/blockchain technologies

• Work in collaboration with the application team and integration team to design, create, and maintain optimal data pipeline architecture and data structures for Data Lake/Data Warehouse.
• Work with stakeholders including the Sales, Product, and Customer Support teams to assist with data-related technical issues and support their data analytics needs.
• Assemble large, complex data sets from third-party vendors to meet 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, Elasticsearch, MongoDB, and AWS technology.
• Streamline existing and introduce enhanced reporting and analysis solutions that leverage complex data sources derived from multiple internal systems.

• 5+ years of experience in a Data Engineer role.
• Proficiency in Linux.
• Must have SQL knowledge and experience working with relational databases, query authoring (SQL) as well as familiarity with databases including Mysql, Mongo, Cassandra, and Athena.
• Must have experience with Python/Scala.
• Must have experience with Big Data technologies like Apache Spark.
• Must have experience with Apache Airflow.
• Experience with data pipeline and ETL tools like AWS Glue.
• Experience working with AWS cloud services: EC2, S3, RDS, Redshift.

Key deliverables for the Data Science Engineer would be to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be on applying data mining techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products.

What will you do?

• You will be building and deploying ML models to solve specific business problems related to NLP, computer vision, and fraud detection.
• You will be constantly assessing and improving the model using techniques like Transfer learning
• You will identify valuable data sources and automate collection processes along with undertaking pre-processing of structured and unstructured data
• You will own the complete ML pipeline - data gathering/labeling, cleaning, storage, modeling, training/testing, and deployment.
• Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
• Building predictive models and machine-learning algorithms to apply to data sets.
• Coordinate with different functional teams to implement models and monitor outcomes.
•  
• Presenting information using data visualization techniques and proposing solutions and strategies to business challenges

We would love to hear from you if :

• You have 2+ years of experience as a software engineer at a SaaS or technology company
• Demonstrable hands-on programming experience with Python/R Data Science Stack
• Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python
• Familiarity with Big Data Platforms (Databricks, Hadoop, Hive), AWS Services (AWS, Sagemaker, IAM, S3, Lambda Functions, Redshift, Elasticsearch)
• Experience in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests.
• Demonstrable competency in Data Visualisation using the Python/R Data Science Stack.
• Preferable Experience Experienced in web crawling and data scraping
• Strong experience in NLP. Worked on libraries such as NLTK, Spacy, Pattern, Gensim etc.
• Experience with text mining, pattern matching and fuzzy matching

• Brand new Macbook
• Stock Options
• Health Insurance
• Unlimited Sick Leaves
• Passion Fund (Invest in yourself or your passion project)
• Wind Down

• Analyze and organize raw data 
• Build data systems and pipelines
• Evaluate business needs and objectives
• Interpret trends and patterns
• Conduct complex data analysis and report on results 
• Build algorithms and prototypes
• Combine raw information from different sources
• Explore ways to enhance data quality and reliability
• Identify opportunities for data acquisition
• Should have experience in Python, Django Micro Service Senior developer with Financial Services/Investment Banking background.
• Develop analytical tools and programs
• Collaborate with data scientists and architects on several projects
• Should have 5+ years of experience as a data engineer or in a similar role
• Technical expertise with data models, data mining, and segmentation techniques
• Should have experience programming languages such as Python
• Hands-on experience with SQL database design
• Great numerical and analytical skills
• Degree in Computer Science, IT, or similar field; a Master’s is a plus
• Data engineering certification (e.g. IBM Certified Data Engineer) is a plus

About LodgIQ

LodgIQ is led by a team of experienced hospitality technology experts, data scientists and product domain experts. Seed funded by Highgate Ventures, a venture capital platform focused on early stage technology investments in the hospitality industry and Trilantic Capital Partners, a global private equity firm, LodgIQ has made a significant investment in advanced machine learning platforms and data science.

Title : Data Scientist

• Apply Data Science and Machine Learning to a REAL-LIFE  problem  - “Predict Guest Arrivals and Determine Best Prices for Hotels”
• Apply advanced analytics in a BIG Data Environment – AWS, MongoDB, SKLearn
• Help scale up the product in a global offering across 100+  global markets

• Minimum 3 years of experience with advanced data analytic techniques, including data mining, machine learning, statistical analysis, and optimization.    Student projects are acceptable.
• At least 1 year of experience with Python / Numpy / Pandas / Scipy/ MatPlotLib / Scikit-Learn
•   Experience in working with massive data sets, including structured and unstructured with at least 1 prior engagement involving data gathering, data cleaning, data mining, and data visualization
•   Solid grasp over  optimization techniques
•   Master's  or PhD degree in Business Analytics.  Data science, Statistics or Mathematics
•   Ability to show a track record of solving large, complex problems

• Does analytics to extract insights from raw historical data of the organization. 
• Generates usable training dataset for any/all MV projects with the help of Annotators, if needed.
• Analyses user trends, and identifies their biggest bottlenecks in Hammoq Workflow.
• Tests the short/long term impact of productized MV models on those trends.
• Skills - Numpy, Pandas, SPARK, APACHE SPARK, PYSPARK, ETL mandatory. 

REQUIREMENT:

•  Previous experience of working in large scale data engineering
•  4+ years of experience working in data engineering and/or backend technologies with cloud experience (any) is mandatory.
•  Previous experience of architecting and designing backend for large scale data processing.
•  Familiarity and experience of working in different technologies related to data engineering – different database technologies, Hadoop, spark, storm, hive etc.
•  Hands-on and have the ability to contribute a key portion of data engineering backend.
•  Self-inspired and motivated to drive for exceptional results.
•  Familiarity and experience working with different stages of data engineering – data acquisition, data refining, large scale data processing, efficient data storage for business analysis.
•  Familiarity and experience working with different DB technologies and how to scale them.

RESPONSIBILITY:

•  End to end responsibility to come up with data engineering architecture, design, development and then implementation of it.
•  Build data engineering workflow for large scale data processing.
•  Discover opportunities in data acquisition.
•  Bring industry best practices for data engineering workflow.
•  Develop data set processes for data modelling, mining and production.
•  Take additional tech responsibilities for driving an initiative to completion
•  Recommend ways to improve data reliability, efficiency and quality
•  Goes out of their way to reduce complexity.
•  Humble and outgoing - engineering cheerleaders.