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.

Location:  Chennai
Education: BE/BTech
Experience: Minimum 3+ years of experience as a Data Scientist/Data Engineer

Domain knowledge: Data cleaning, modelling, analytics, statistics, machine learning, AI

Requirements:

• To be part of Digital Manufacturing and Industrie 4.0 projects across client group of companies
• Design and develop AI//ML models to be deployed across factories
• Knowledge on Hadoop, Apache Spark, MapReduce, Scala, Python programming, SQL and NoSQL databases is required
• Should be strong in statistics, data analysis, data modelling, machine learning techniques and Neural Networks
• Prior experience in developing AI and ML models is required
• Experience with data from the Manufacturing Industry would be a plus

Roles and Responsibilities:

• Develop AI and ML models for the Manufacturing Industry with a focus on Energy, Asset Performance Optimization and Logistics
• Multitasking, good communication necessary
• Entrepreneurial attitude

• Job Location:                      Chennai
• Reporting to:                      Team Leader, Energy Management System

Seeking Data Analytics Trainer with Power BI and Tableau Expertise

Experience Required: Minimum 3 Years

Location: Indore

Part-Time / Full-Time Availability

We are actively seeking a qualified candidate to join our team as a Data Analytics Trainer, with a strong focus on Power BI and Tableau expertise. The ideal candidate should possess the following qualifications:

  A track record of 3 to 6 years in delivering technical training and mentoring.

  Profound understanding of Data Analytics concepts.

  Strong proficiency in Excel and Advanced Excel.

  Demonstrated hands-on experience and effective training skills in Python, Data Visualization, R Programming, and an in-depth understanding of both Power BI and Tableau.

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https://www.linkedin.com/in/shweta-bharti-a105ab197/

Position: ETL Developer

Location: Mumbai

Exp.Level: 4+ Yrs

Required Skills:

* Strong scripting knowledge such as: Python and Shell

* Strong relational database skills especially with DB2/Sybase

* Create high quality and optimized stored procedures and queries

* Strong with scripting language such as Python and Unix / K-Shell

* Strong knowledge base of relational database performance and tuning such as: proper use of indices, database statistics/reorgs, de-normalization concepts.

* Familiar with lifecycle of a trade and flows of data in an investment banking operation is a plus.

* Experienced in Agile development process

* Java Knowledge is a big plus but not essential

* Experience in delivery of metrics / reporting in an enterprise environment (e.g. demonstrated experience in BI tools such as Business Objects, Tableau, report design & delivery) is a plus

* Experience on ETL processes and tools such as Informatica is a plus. Real time message processing experience is a big plus.

* Good team player; Integrity & ownership

Skills and requirements

• Experience analyzing complex and varied data in a commercial or academic setting.
• Desire to solve new and complex problems every day.
• Excellent ability to communicate scientific results to both technical and non-technical team members.

Desirable

• A degree in a numerically focused discipline such as, Maths, Physics, Chemistry, Engineering or Biological Sciences..
• Hands on experience on Python, Pyspark, SQL
• Hands on experience on building End to End Data Pipelines.
• Hands on Experience on Azure Data Factory, Azure Data Bricks, Data Lake - added advantage
• Hands on Experience in building data pipelines.
• Experience with Bigdata Tools, Hadoop, Hive, Sqoop, Spark, SparkSQL
• Experience with SQL or NoSQL databases for the purposes of data retrieval and management.
• Experience in data warehousing and business intelligence tools, techniques and technology, as well as experience in diving deep on data analysis or technical issues to come up with effective solutions.
• BS degree in math, statistics, computer science or equivalent technical field.
• Experience in data mining structured and unstructured data (SQL, ETL, data warehouse, Machine Learning etc.) in a business environment with large-scale, complex data sets.
• Proven ability to look at solutions in unconventional ways. Sees opportunities to innovate and can lead the way.
• Willing to learn and work on Data Science, ML, AI.

Specialism- Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, python, decision tree, random forest, SAS, clustering classification

Senior Analytics Consultant- Responsibilities

• Understand business problem and requirements by building domain knowledge and translate to data science problem
• Conceptualize and design cutting edge data science solution to solve the data science problem, apply design thinking concepts
• Identify the right algorithms , tech stack , sample outputs required to efficiently adder the end need
• Prototype and experiment the solution to successfully demonstrate the value
  Independently or with support from team execute the conceptualized solution as per plan by following project management guidelines
• Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization
• Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development , practice development initiatives

Job Description for :

Role: Data/Integration Architect

Experience – 8-10 Years

Notice Period: Under 30 days

Key Responsibilities: Designing, Developing frameworks for batch and real time jobs on Talend. Leading migration of these jobs from Mulesoft to Talend, maintaining best practices for the team, conducting code reviews and demos.

Core Skillsets:

Talend Data Fabric - Application, API Integration, Data Integration. Knowledge on Talend Management Cloud, deployment and scheduling of jobs using TMC or Autosys.

Programming Languages - Python/Java
Databases: SQL Server, Other Databases, Hadoop

Should have worked on Agile

Sound communication skills

Should be open to learning new technologies based on business needs on the job

Additional Skills:

Awareness of other data/integration platforms like Mulesoft, Camel

Awareness Hadoop, Snowflake, S3

• 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