11+ OLAP Jobs in Mumbai | OLAP Job openings in Mumbai

• Key responsibility is to design, develop & maintain efficient Data models for the organization maintained to ensure optimal query performance by the consumption layer.
• Developing, Deploying & maintaining a repository of UDXs written in Java / Python.
• Develop optimal Data Model design, analyzing complex distributed data deployments, and making recommendations to optimize performance basis data consumption patterns, performance expectations, the query is executed on the tables/databases, etc.
• Periodic Database health check and maintenance
• Designing collections in a no-SQL Database for efficient performance
• Document & maintain data dictionary from various sources to enable data governance
• Coordination with Business teams, IT, and other stakeholders to provide best-in-class data pipeline solutions, exposing data via APIs, loading in down streams, No-SQL Databases, etc
• Data Governance Process Implementation and ensuring data security

Requirements

• Extensive working experience in Designing & Implementing Data models in OLAP Data Warehousing solutions (Redshift, Synapse, Snowflake, Teradata, Vertica, etc).
• Programming experience using Python / Java.
• Working knowledge in developing & deploying User-defined Functions (UDXs) using Java / Python.
• Strong understanding & extensive working experience in OLAP Data Warehousing (Redshift, Synapse, Snowflake, Teradata, Vertica, etc) architecture and cloud-native Data Lake (S3, ADLS, BigQuery, etc) Architecture.
• Strong knowledge in Design, Development & Performance tuning of 3NF/Flat/Hybrid Data Model.
• Extensive technical experience in SQL including code optimization techniques.
• Strung knowledge of database performance and tuning, troubleshooting, and tuning.
• Knowledge of collection design in any No-SQL DB (DynamoDB, MongoDB, CosmosDB, etc), along with implementation of best practices.
• Ability to understand business functionality, processes, and flows.
• Good combination of technical and interpersonal skills with strong written and verbal communication; detail-oriented with the ability to work independently.
• Any OLAP DWH DBA Experience and User Management will be added advantage.
• Knowledge in financial industry-specific Data models such as FSLDM, IBM Financial Data Model, etc will be added advantage.
• Experience in Snowflake will be added advantage.
• Working experience in BFSI/NBFC & data understanding of Loan/Mortgage data will be added advantage.

Functional knowledge

• Data Governance & Quality Assurance
• Modern OLAP Database Architecture & Design
• Linux
• Data structures, algorithm & data modeling techniques
• No-SQL database architecture
• Data Security

Job Title: Credit Risk Analyst

Company: FatakPay FinTech

Location: Mumbai, India

Salary Range: INR 8 - 15 Lakhs per annum

Job Description:

FatakPay, a leading player in the fintech sector, is seeking a dynamic and skilled Credit Risk Analyst to join our team in Mumbai. This position is tailored for professionals who are passionate about leveraging technology to enhance financial services. If you have a strong background in engineering and a keen eye for risk management, we invite you to be a part of our innovative journey.

Key Responsibilities:

• Conduct thorough risk assessments by analyzing borrowers' financial data, including financial statements, credit scores, and income details.
• Develop and refine predictive models using advanced statistical methods to forecast loan defaults and assess creditworthiness.
• Collaborate in the formulation and execution of credit policies and risk management strategies, ensuring compliance with regulatory standards.
• Monitor and analyze the performance of loan portfolios, identifying trends, risks, and opportunities for improvement.
• Stay updated with financial regulations and standards, ensuring all risk assessment processes are in compliance.
• Prepare comprehensive reports on credit risk analyses and present findings to senior management.
• Work closely with underwriting, finance, and sales teams to provide critical input influencing lending decisions.
• Analyze market trends and economic conditions, adjusting risk assessment models and strategies accordingly.
• Utilize cutting-edge financial technologies for more efficient and accurate data analysis.
• Engage in continual learning to stay abreast of new tools, techniques, and best practices in credit risk management.

Qualifications:

• Minimum qualification: B.Tech or Engineering degree from a reputed institution.
• 2-4 years of experience in credit risk analysis, preferably in a fintech environment.
• Proficiency in data analysis, statistical modeling, and machine learning techniques.
• Strong analytical and problem-solving skills.
• Excellent communication skills, with the ability to present complex data insights clearly.
• A proactive approach to work in a fast-paced, technology-driven environment.
• Up-to-date knowledge of financial regulations and compliance standards.

We look forward to discovering how your expertise and innovative ideas can contribute to the growth and success of FatakPay. Join us in redefining the future of fintech!

Mandatory Skills: Azure Data Lake Storage, Azure SQL databases, Azure Synapse, Data Bricks (Pyspark/Spark), Python, SQL, Azure Data Factory.

Good to have: Power BI, Azure IAAS services, Azure Devops, Microsoft Fabric

Ø Very strong understanding on ETL and ELT

Ø Very strong understanding on Lakehouse architecture.

Ø Very strong knowledge in Pyspark and Spark architecture.

Ø Good knowledge in Azure data lake architecture and access controls

Ø Good knowledge in Microsoft Fabric architecture

Ø Good knowledge in Azure SQL databases

Ø Good knowledge in T-SQL

Ø Good knowledge in CI /CD process using Azure devops

Ø Power BI

• Act as primary day-to-day contact on analytics to agency-client leads
• Develop bespoke analytics proposals for presentation to agencies & clients, for delivery within the teams
• Ensure delivery of projects and services across the analytics team meets our stakeholder requirements (time, quality, cost)
• Hands on platforms to perform data pre-processing that involves data transformation as well as data cleaning
  
• Ensure data quality and integrity
  
• Interpret and analyse data problems
  
• Build analytic systems and predictive models
  
• Increasing the performance and accuracy of machine learning algorithms through fine-tuning and further
  
• Visualize data and create reports
  
• Experiment with new models and techniques
  
• Align data projects with organizational goals

• Min 6 - 7 years’ experience working in Data Science
• Prior experience as a Data Scientist within a digital media is desirable
• Solid understanding of machine learning
• A degree in a quantitative field (e.g. economics, computer science, mathematics, statistics, engineering, physics, etc.)
• Experience with SQL/ Big Query/GMP tech stack / Clean rooms such as ADH
• A knack for statistical analysis and predictive modelling
• Good knowledge of R, Python
• Experience with SQL, MYSQL, PostgreSQL databases
• Knowledge of data management and visualization techniques
• Hands-on experience on BI/Visual Analytics Tools like PowerBI or Tableau or Data Studio
• Evidence of technical comfort and good understanding of internet functionality desirable
• Analytical pedigree - evidence of having approached problems from a mathematical perspective and working through to a solution in a logical way
• Proactive and results-oriented
• A positive, can-do attitude with a thirst to continually learn new things
• An ability to work independently and collaboratively with a wide range of teams
• Excellent communication skills, both written and oral

Minimum of 8 years of experience of which, 4 years should be of applied data mining

experience in disciplines such as Call Centre Metrics.

 Strong experience in advanced statistics and analytics including segmentation, modelling, regression, forecasting etc.

 Experience with leading and managing large teams.

 Demonstrated pattern of success in using advanced quantitative analytic methods to solve business problems.

 Demonstrated experience with Business Intelligence/Data Mining tools to work with

data, investigate anomalies, construct data sets, and build models.

 Critical to share details on projects undertaken (preferably on telecom industry)

specifically through analysis from CRM.

Responsibilities

1. Create data funnels to feed into models via web, structured and unstructured data
2. Maintain coding standards using  SDLC, Git, AWS deployments etc
3. Keep abreast of developments in the field
4. Deploy models in production and monitor them
5. Documentations of processes and logic
6. Take ownership of the solution from code to deployment and performance

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

We’re looking to hire someone to help scale Machine Learning and NLP efforts at Episource. You’ll work with the team that develops the models powering Episource’s product focused on NLP driven medical coding. Some of the problems include improving our ICD code recommendations , clinical named entity recognition and information extraction from clinical notes.

This is a role for highly technical machine learning & data engineers who combine outstanding oral and written communication skills, and the ability to code up prototypes and productionalize using a large range of tools, algorithms, and languages. Most importantly they need to have the ability to autonomously plan and organize their work assignments based on high-level team goals.

You will be responsible for setting an agenda to develop and ship machine learning models that positively impact the business, working with partners across the company including operations and engineering. You will use research results to shape strategy for the company, and help build a foundation of tools and practices used by quantitative staff across the company.

What you will achieve:

• Define the research vision for data science, and oversee planning, staffing, and prioritization to make sure the team is advancing that roadmap

• Invest in your team’s skills, tools, and processes to improve their velocity, including working with engineering counterparts to shape the roadmap for machine learning needs

• Hire, retain, and develop talented and diverse staff through ownership of our data science hiring processes, brand, and functional leadership of data scientists

• Evangelise machine learning and AI internally and externally, including attending conferences and being a thought leader in the space

• Partner with the executive team and other business leaders to deliver cross-functional research work and models

Required Skills:

• Strong background in classical machine learning and machine learning deployments is a must and preferably with 4-8 years of experience

• Knowledge of deep learning & NLP

• Hands-on experience in TensorFlow/PyTorch, Scikit-Learn, Python, Apache Spark & Big Data platforms to manipulate large-scale structured and unstructured datasets.

• Experience with GPU computing is a plus.

• Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization. This could be through technical leadership with ownership over a research agenda, or developing a team as a personnel manager in a new area at a larger company.

• Expert-level experience with a wide range of quantitative methods that can be applied to business problems.

• Evidence you’ve successfully been able to scope, deliver and sell your own research in a way that shifts the agenda of a large organization.

• Excellent written and verbal communication skills on quantitative topics for a variety of audiences: product managers, designers, engineers, and business leaders.

• Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling

Qualifications

• Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization

• Expert-level experience with machine learning that can be applied to business problems

• Evidence you’ve successfully been able to scope, deliver and sell your own work in a way that shifts the agenda of a large organization

• Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling

• Degree in a field that has very applicable use of data science / statistics techniques (e.g. statistics, applied math, computer science, OR a science field with direct statistics application)

• 5+ years of industry experience in data science and machine learning, preferably at a software product company

• 3+ years of experience managing data science teams, incl. managing/grooming managers beneath you

• 3+ years of experience partnering with executive staff on data topics