Data Analyst

Responsibilities include: 

• Convert the machine learning models into application program interfaces (APIs) so that other applications can use it
• Build AI models from scratch and help the different components of the organization (such as product managers and stakeholders) understand what results they gain from the model
• Build data ingestion and data transformation infrastructure
• Automate infrastructure that the data science team uses
• Perform statistical analysis and tune the results so that the organization can make better-informed decisions
• Set up and manage AI development and product infrastructure
• Be a good team player, as coordinating with others is a must

Data Scientist-

We are looking for an experienced Data Scientists to join our engineering team and

help us enhance our mobile application with data. In this role, we're looking for

people who are passionate about developing ML/AI in various domains that solves

enterprise problems. We are keen on hiring someone who loves working in fast paced start-up environment and looking to solve some challenging engineering

problems.

As one of the earliest members in engineering, you will have the flexibility to design

the models and architecture from ground up. As any early-stage start-up, we expect

you to be comfortable wearing various hats, and be proactive contributor in building

something truly remarkable.

Responsibilities

Researches, develops and maintains machine learning and statistical models for

business requirements

Work across the spectrum of statistical modelling including supervised,

unsupervised, & deep learning techniques to apply the right level of solution to

the right problem Coordinate with different functional teams to monitor outcomes and refine/

improve the machine learning models Implements models to uncover patterns and predictions creating business value and innovation

Identify unexplored data opportunities for the business to unlock and maximize

the potential of digital data within the organization

Develop NLP concepts and algorithms to classify and summarize structured/unstructured text data

Qualifications

3+ years of experience solving complex business problems using machine

learning.

Fluency in programming languages such as Python, NLP and Bert, is a must

Strong analytical and critical thinking skills

Experience in building production quality models using state-of-the-art technologies 

Familiarity with databases like MySQL, Oracle, SQL Server, NoSQL, etc. is

desirable Ability to collaborate on projects and work independently when required.

Previous experience in Fintech/payments domain is a bonus

You should have Bachelor’s or Master’s degree in Computer Science, Statistics

or Mathematics or another quantitative field from a top tier Institute

What you’ll do

• Deliver plugins for our Python-based ETL pipelines.
• Deliver Python microservices for provisioning and managing cloud infrastructure.
• Implement algorithms to analyse large data sets.
• Draft design documents that translate requirements into code.
• Deal with challenges associated with handling large volumes of data.
• Assume responsibilities from technical design through technical client support.
• Manage expectations with internal stakeholders and context-switch in a fast paced environment.
• Thrive in an environment that uses AWS and Elasticsearch extensively.
• Keep abreast of technology and contribute to the engineering strategy.
• Champion best development practices and provide mentorship.

What we’re looking for

• Experience in Python 3.
• Python libraries used for data (such as pandas, numpy).
• AWS.
• Elasticsearch.
• Performance tuning.
• Object Oriented Design and Modelling.
• Delivering complex software, ideally in a FinTech setting.
• CI/CD tools.
• Knowledge of design patterns.
• Sharp analytical and problem-solving skills.
• Strong sense of ownership.
• Demonstrable desire to learn and grow.
• Excellent written and oral communication skills.
• Mature collaboration and mentoring abilities.

About SteelEye Culture

• Work from home until you are vaccinated against COVID-19
• Top of the line health insurance • Order discounted meals every day from a dedicated portal
• Fair and simple salary structure
• 30+ holidays in a year
• Fresh fruits every day
• Centrally located. 5 mins to the nearest metro station (MG Road)
• Measured on output and not input

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