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Roles and

Responsibilities

Seeking AWS Cloud Engineer /Data Warehouse Developer for our Data CoE team to

help us in configure and develop new AWS environments for our Enterprise Data Lake,

migrate the on-premise traditional workloads to cloud. Must have a sound

understanding of BI best practices, relational structures, dimensional data modelling,

structured query language (SQL) skills, data warehouse and reporting techniques.

 Extensive experience in providing AWS Cloud solutions to various business

use cases.

 Creating star schema data models, performing ETLs and validating results with

business representatives

 Supporting implemented BI solutions by: monitoring and tuning queries and

data loads, addressing user questions concerning data integrity, monitoring

performance and communicating functional and technical issues.

Job Description: -

This position is responsible for the successful delivery of business intelligence

information to the entire organization and is experienced in BI development and

implementations, data architecture and data warehousing.

Requisite Qualification

Essential

-

AWS Certified Database Specialty or -

AWS Certified Data Analytics

Preferred

Any other Data Engineer Certification

Requisite Experience

Essential 4 -7 yrs of experience

Preferred 2+ yrs of experience in ETL & data pipelines

Skills Required

Special Skills Required

 AWS: S3, DMS, Redshift, EC2, VPC, Lambda, Delta Lake, CloudWatch etc.

 Bigdata: Databricks, Spark, Glue and Athena

 Expertise in Lake Formation, Python programming, Spark, Shell scripting

 Minimum Bachelor’s degree with 5+ years of experience in designing, building,

and maintaining AWS data components

 3+ years of experience in data component configuration, related roles and

access setup

 Expertise in Python programming

 Knowledge in all aspects of DevOps (source control, continuous integration,

deployments, etc.)

 Comfortable working with DevOps: Jenkins, Bitbucket, CI/CD

 Hands on ETL development experience, preferably using or SSIS

 SQL Server experience required

 Strong analytical skills to solve and model complex business requirements

 Sound understanding of BI Best Practices/Methodologies, relational structures,

dimensional data modelling, structured query language (SQL) skills, data

warehouse and reporting techniques

Preferred Skills

Required

 Experience working in the SCRUM Environment.

 Experience in Administration (Windows/Unix/Network/Database/Hadoop) is a

plus.

 Experience in SQL Server, SSIS, SSAS, SSRS

 Comfortable with creating data models and visualization using Power BI

 Hands on experience in relational and multi-dimensional data modelling,

including multiple source systems from databases and flat files, and the use of

standard data modelling tools

 Ability to collaborate on a team with infrastructure, BI report development and

business analyst resources, and clearly communicate solutions to both

technical and non-technical team members

Title:- Data Scientist

Experience:-6 years

Work Mode:- Onsite

Primary Skills:- Data Science, SQL, Python, Data Modelling, Azure, AWS, Banking Domain (BFSI/NBFC)

Qualification:- Any

Roles & Responsibilities:-

1.  Acquiring, cleaning, and preprocessing raw data for analysis.

2.  Utilizing statistical methods and tools for analyzing and interpreting complex  datasets.

3.  Developing and implementing machine learning models for predictive analysis.

4.  Creating visualizations to effectively communicate insights to both technical and   non-technical stakeholders.

5.  Collaborating with cross-functional teams, including data engineers, business   analysts, and domain experts.

6.  Evaluating and optimizing the performance of machine learning models for   accuracy and efficiency.

7.  Identifying patterns and trends within data to inform business decision-making.

8.  Staying updated on the latest advancements in data science, machine learning, and  relevant technologies.

Requirement:- 

1.  Experience with modeling techniques such as Linear Regression, clustering, and classification techniques.

2.  Must have a passion for data, structured or unstructured.  0.6 – 5 years of hands-on experience with Python and SQL is a must.

3.   Should have sound experience in data mining, data analysis and machine learning techniques.

4.  Excellent critical thinking, verbal and written communications skills.

5.  Ability and desire to work in a proactive, highly engaging, high-pressure, client service environment.

6.   Good presentation skills.

About Us:

We are a VC-funded startup solving one of the biggest transportation problems India faces. Most passengers in India travel long distance by IRCTC trains. At time of booking, approx 1 out of every 2 passengers end up with a Waitlisted or RAC ticket. This creates a lot of anxiety for passengers, as Railway only announces only 4 hour before departure if they have a confirmed seat. We solve this problem through our Waitlist & RAC Protection. Protection can be bought against each IRCTC ticket at time of booking. If train ticket is not confirmed, we fly the passenger to the destination. Our team consists of 3 Founders from IIT, IIM and ISB.

Functional Experience:

• Computer Science or IT Engineering background with solid understanding of basics of Data Structures and Algorithms
• 2+ years of data science experience working with large datasets
• Expertise in Python packages like pandas, numPy, sklearn, matplotlib, seaborn, keras and tensorflow
• Expertise in Big Data technologies like Hadoop, Cassandra and PostgreSQL
• Expertise in Cloud computing on AWS with EC2, AutoML, Lambda and RDS
• Good knowledge of Machine Learning and Statistical time series analysis (optional)
• Unparalleled logical ability making you the go to guy for all things related to data
• You love coding like a hobby and are up for a challenge!

Cultural:

• Assume a strong sense of ownership of analytics : Design, develop & deploy
• Collaborate with senior management, operations & business team
• Ensure Quality & sustainability of the architecture
• Motivation to join an early stage startup should go beyond compensation

Roles and Responsibilities

• Managing available resources such as hardware, data, and personnel so that deadlines are met.
• Analyzing the ML and Deep Learning algorithms that could be used to solve a given problem and ranking them by their success probabilities
• Exploring data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
• Defining validation framework and establish a process to ensure acceptable data quality criteria are met
• Supervising the data acquisition and partnership roadmaps to create stronger product for our customers.
• Defining feature engineering process to ensure usage of meaningful features given the business constraints which may vary by market
• Device self-learning strategies through analysis of errors from the models
• Understand business issues and context, devise a framework for solving unstructured problems and articulate clear and actionable solutions underpinned by analytics.
• Manage multiple projects simultaneously while demonstrating business leadership to collaborate & coordinate with different functions to deliver the solutions in a timely, efficient and effective manner.
• Manage project resources optimally to deliver projects on time; drive innovation using residual resources to create strong solution pipeline; provide direction, coaching & training, feedbacks to project team members to enhance performance, support development and encourage value aligned behaviour of the project team members; Provide inputs for periodic performance appraisal of project team members.

Preferred Technical & Professional expertise

• Undergraduate Degree in Computer Science / Engineering / Mathematics / Statistics / economics or other quantitative fields
• At least 2+ years of experience of managing Data Science projects with specializations in Machine Learning
• In-depth knowledge of cloud analytics tools.
• Able to drive Python Code optimization; ability review codes and provide inputs to improve the quality of codes
• Ability to evaluate hardware selection for running ML models for optimal performance
• Up to date with Python libraries and versions for machine learning; Extensive hands-on experience with Regressors; Experience working with data pipelines.
• Deep knowledge of math, probability, statistics and algorithms; Working knowledge of Supervised Learning, Adversarial Learning and Unsupervised learning
• Deep analytical thinking with excellent problem-solving abilities
• Strong verbal and written communication skills with a proven ability to work with all levels of management; effective interpersonal and influencing skills.
• Ability to manage a project team through effectively allocation of tasks, anticipating risks and setting realistic timelines for managing the expectations of key stakeholders
• Strong organizational skills and an ability to balance and handle multiple concurrent tasks and/or issues simultaneously.
• Ensure that the project team understand and abide by compliance framework for policies, data, systems etc. as per group, region and local standards

• Collaborate with the business teams to understand the data environment in the organization; develop and lead the Data Scientists team to test and scale new algorithms through pilots and subsequent scaling up of the solutions
• Influence, build and maintain the large-scale data infrastructure required for the AI projects, and integrate with external IT infrastructure/service
• Act as the single point source for all data related queries; strong understanding of internal and external data sources; provide inputs in deciding data-schemas
• Design, develop and maintain the framework for the analytics solutions pipeline
• Provide inputs to the organization’s initiatives on data quality and help implement frameworks and tools for the various related initiatives
• Work in cross-functional teams of software/machine learning engineers, data scientists, product managers, and others to build the AI ecosystem
• Collaborate with the external organizations including vendors, where required, in respect of all data-related queries as well as implementation initiatives

• Minimum 3-4 years of experience with ETL tools, SQL, SSAS & SSIS
• Good understanding of Data Governance, including Master Data Management (MDM) and Data Quality tools and processes
• Knowledge of programming languages eg. JASON, Python, R
• Hands on experience of SQL database design
• Experience working with REST API
• Influencing and supporting project delivery through involvement in project/sprint planning and QA
• Working experience with Azure
• Stakeholder management
• Good communication skills

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