Data Scientist

The Client is the world’s largest media investment company. Our team of experts support clients in programmatic, social, paid search, analytics, technology, organic search, affiliate marketing, e-commerce and across traditional channel We are currently looking for a Manager Analyst – Analytics to join us. In this role, you will work on

various projects for the in-house team across data management, reporting, and analytics.

Responsibility:

•       Serve as a Subject Matter Expert on data usage – extraction, manipulation, and inputs for analytics

•       Develop data extraction and manipulation code based on business rules

•       Design and construct data store and procedures for their maintenance  Develop and maintain strong relationships with stakeholders  Write high-quality code as per prescribed standards.

•       Participate in internal projects as required

Requirements:

•       2-5 years for strong experience in working with SQL, Python, ETL development.

•       Strong Experience in writing complex SQLs

•       Good Communication skills

•       Good experience of working with any BI tool like Tableau, Power BI.

•       Familiar with various cloud technologies and their offerings within the data specialization and Data Warehousing.

•       Snowflake, AWS are good to have.

Minimum qualifications:

•       B. Tech./MCA or equivalent preferred

Excellent 2 years Hand on experience on Big data, ETL Development, Data Processing.  

Job Title: Data Analyst with Python

Experience: 4+ years

Location: Mumbai

Working Mode: Onsite

Primary Skills: Python, Data Analysis of RDs, FDs, Saving Accounts, Banking domain, Risk Consultant, Car Loan Model, Cross-sell model

Qualification: Any graduation

Job Description

1. With 4 to 5 years of banking analytics experience

2. Data Analyst profile with good domain understanding

3. Good with Python and worked on Liabilities (Mandatory)

4. For Liabilities Should have worked on (Saving A/c, FD,RD) (Mandatory)

5. Good with stakeholder management and requirement gathering

6. Only from banking industry

Looking for freelance?

We are seeking a freelance Data Engineer with 7+ years of experience

Skills Required: Deep knowledge in any cloud (AWS, Azure , Google cloud), Data bricks, Data lakes, Data Ware housing Python/Scala , SQL, BI, and other analytics systems

What we are looking for

We are seeking an experienced Senior Data Engineer with experience in architecture, design, and development of highly scalable data integration and data engineering processes

• The Senior Consultant must have a strong understanding and experience with data & analytics solution architecture, including data warehousing, data lakes, ETL/ELT workload patterns, and related BI & analytics systems
• Strong in scripting languages like Python, Scala
• 5+ years of hands-on experience with one or more of these data integration/ETL tools.
• Experience building on-prem data warehousing solutions.
• Experience with designing and developing ETLs, Data Marts, Star Schema
• Designing a data warehouse solution using Synapse or Azure SQL DB
• Experience building pipelines using Synapse or Azure Data Factory to ingest data from various sources
• Understanding of integration run times available in Azure.
• Advanced working SQL knowledge and experience working with relational databases, and queries. authoring (SQL) as well as working familiarity with a variety of database

• 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

• 4+ years of experience Solid understanding of Python, Java and general software development skills (source code management, debugging, testing, deployment etc.).
• Experience in working with Solr and ElasticSearch Experience with NLP technologies & the handling of unstructured text Detailed understanding of text pre-processing and normalisation techniques such as tokenisation, lemmatisation, stemming, POS tagging etc.
• Prior experience in implementation of traditional ML solutions - classification, regression or clustering problem Expertise in text-analytics - Sentiment Analysis, Entity Extraction, Language modelling - and associated sequence learning models ( RNN, LSTM, GRU).
• Comfortable working with deep-learning libraries (eg. PyTorch)
• Candidate can even be a fresher with 1 or 2 years of experience IIIT, IIIT, Bits Pilani, top 5 local colleges are preferred colleges and universities.
• A Masters candidate in machine learning.
• Can source candidates from Mu Sigma and Manthan.

Primary Responsibilities

• Understand current state architecture, including pain points.
• Create and document future state architectural options to address specific issues or initiatives using Machine Learning.
• Innovate and scale architectural best practices around building and operating ML workloads by collaborating with stakeholders across the organization.
• Develop CI/CD & ML pipelines that help to achieve end-to-end ML model development lifecycle from data preparation and feature engineering to model deployment and retraining.
• Provide recommendations around security, cost, performance, reliability, and operational efficiency and implement them
• Provide thought leadership around the use of industry standard tools and models (including commercially available models and tools) by leveraging experience and current industry trends.
• Collaborate with the Enterprise Architect, consulting partners and client IT team as warranted to establish and implement strategic initiatives.
• Make recommendations and assess proposals for optimization.
• Identify operational issues and recommend and implement strategies to resolve problems.

Must have:

• 3+ years of experience in developing CI/CD & ML pipelines for end-to-end ML model/workloads development
• Strong knowledge in ML operations and DevOps workflows and tools such as Git, AWS CodeBuild & CodePipeline, Jenkins, AWS CloudFormation, and others
• Background in ML algorithm development, AI/ML Platforms, Deep Learning, ML Operations in the cloud environment.
• Strong programming skillset with high proficiency in Python, R, etc.
• Strong knowledge of AWS cloud and its technologies such as S3, Redshift, Athena, Glue, SageMaker etc.
• Working knowledge of databases, data warehouses, data preparation and integration tools, along with big data parallel processing layers such as Apache Spark or Hadoop
• Knowledge of pure and applied math, ML and DL frameworks, and ML techniques, such as random forest and neural networks
• Ability to collaborate with Data scientist, Data Engineers, Leaders, and other IT teams
• Ability to work with multiple projects and work streams at one time. Must be able to deliver results based upon project deadlines.
• Willing to flex daily work schedule to allow for time-zone differences for global team communications
• Strong interpersonal and communication skills

Key Responsibilities:

• Partnering with clients and internal business owners (product, marketing, edit, etc.) to understand needs and develop models and products for Kaleidofin business line.
• 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, hyperparameter tuning, ensembling 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.
• Collaborate with the team to improve the effectiveness of business decisions using data and machine learning/predictive modeling.
• Innovate on projects by using new modeling techniques or tools.
• Utilize effective project planning techniques to break down complex projects into tasks and ensure deadlines are kept.
• Communicate findings to team and leadership to ensure models are well understood and incorporated into business processes.

Skills:

• 2+ year 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, Boosting trees, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, 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 scoring domains preferred