SDE1 Data Scientist

Role - Senior Analytics Executive

Experience - 1-2 years

Location - Open (Remote working option available)

About Company :-

Our team is made up of best in class digital, offline, and integrated media experts who work together to enhance media's contribution to Google's business. Our team operates in a seamlessly integrated way across strategy, planning, investment, creative, business sciences and analytics, data and technology. The profile of people who work are world class, committed to establishing a new high water mark in the media industry.

About the role/ Some of the things we'd like you to do:

- Support the Analytics team and other stakeholders with analytics agendas impacting campaigns, measurement frameworks, and campaign optimization.

- Conduct thorough data analysis using various tools and software within MFG to provide insights and recommendations that align with client needs.

- Collaborate with internal stakeholders across disciplines and countries to understand client objectives, providing support and expertise in data and analytics while identifying opportunities for advanced analytics solutions.

- Formulate strategic recommendations with the team based on gathered insights, and support the delivery of reporting for clients.

- Continuously improve project performance and processes by collaborating with the team to develop new tools and solutions.

About yourself/ Requirements:

- Bachelor's degree in a related quantitative field (e.g. Statistics, Business Analytics, Economics, Computer Science, etc.)

- 1-2 years of relevant work experience in data analysis; digital media experience desired

- Strong knowledge of various data analysis tools and software (e.g., Excel, SQL, R, Python, Tableau).

- Is proficient in statistical principles and how they apply to tasks/work items.

- Excellent problem-solving skills and the ability to analyze complex data sets.

- Strong communication and interpersonal skills, with the ability to present data-driven insights to both technical and non-technical audiences.

- Ability to work independently and as part of a team, with strong collaboration skills.

- Demonstrated ability to manage multiple projects and prioritize tasks effectively.

- Passion tor continuous learning and staying current with industry trends and best practices in analytics.

Introduction

http://www.synapsica.com/">Synapsica is a https://yourstory.com/2021/06/funding-alert-synapsica-healthcare-ivycap-ventures-endiya-partners/">series-A funded HealthTech startup founded by alumni from IIT Kharagpur, AIIMS New Delhi, and IIM Ahmedabad. We believe healthcare needs to be transparent and objective while being affordable. Every patient has the right to know exactly what is happening in their bodies and they don't have to rely on cryptic 2 liners given to them as a diagnosis. 

Towards this aim, we are building an artificial intelligence enabled cloud based platform to analyse medical images and create v2.0 of advanced radiology reporting.  We are backed by IvyCap, Endia Partners, YCombinator and other investors from India, US, and Japan. We are proud to have GE and The Spinal Kinetics as our partners. Here’s a small sample of what we’re building: https://www.youtube.com/watch?v=FR6a94Tqqls">https://www.youtube.com/watch?v=FR6a94Tqqls 

Your Roles and Responsibilities

We are looking for an experienced MLOps Engineer to join our engineering team and help us create dynamic software applications for our clients. In this role, you will be a key member of a team in decision making, implementations, development and advancement of ML operations of the core AI platform.

• Work closely with a cross functional team to serve business goals and objectives.
• Develop, Implement and Manage MLOps in cloud infrastructure for data preparation,deployment, monitoring and retraining models
• Design and build application containerisation and orchestrate with Docker and Kubernetes in AWS platform. 
• Build and maintain code, tools, packages in cloud

• At Least 2+ years of experience in Data engineering 
• At Least 3+ yr experience in Python with familiarity in popular ML libraries.
• At Least 2+ years experience in model serving and pipelines
• Working knowledge of containers like kubernetes , dockers, in AWS
• Design distributed systems deployment at scale
• Hands-on experience in coding and scripting
• Ability to write effective scalable and modular code.
• Familiarity with Git workflows, CI CD and NoSQL Mongodb
• Familiarity with Airflow, DVC and MLflow is a plus

• Work closely with your business to identify issues and use data to propose solutions for effective decision making
• Build algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organisation.
• Creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc
• Querying databases and using statistical computer languages: R, Python, SLQ, etc.
• Visualizing/presenting data through various Dashboards for Data Analysis, Using Python Dash, Flask etc.
• Test data mining models to select the most appropriate ones for use on a project
• Work in a POSIX/UNIX environment to run/deploy applications
• Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
• Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods
• Horizon scan to stay up to date with the latest technology, techniques and methods
• Coordinate with different functional teams to implement models and monitor outcomes.
• Stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work.

• Able to create algorithms to extract information from large data sets
• Strong knowledge of Python, R, Java or another scripting/statistical languages to automate data retrieval, manipulation and analysis.
• Experience with extracting and aggregating data from large data sets using SQL or other tools
• Strong understanding of various NLP, and NLU techniques like Named Entity Recognition, Summarization, Topic Modeling, Text Classification, Lemmatization and Stemming.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, etc.
• Experience with Python libraries such as Pandas, NumPy, SciPy, Scikit-Learn
• Experience with Jupyter / Pandas / Numpy to manipulate and analyse data
• Knowledge of Machine Learning techniques and their respective pros and cons
• Strong Knowledge of various Data Science Visualization Tools like Tableau, PowerBI, D3, Plotly, etc.
• Experience using web services: Redshift, AWS, S3, Spark, DigitalOcean, etc.
• Proficiency in using query languages, such as SQL, Spark DataFrame API, etc.
• Hands-on experience in HTML, CSS, Bootstrap, JavaScript, AJAX, jQuery and Prototyping.
• Hands-on experience on C#, Javascript, .Net
• Experience in understanding and analyzing data using statistical software (e.g., Python, R, KDB+ and other relevant libraries)
• Experienced in building applications that meet enterprise needs – secure, scalable, loosely coupled design
• Strong knowledge of computer science, algorithms, and design patterns
• Strong oral and written communication, and other soft skills critical to collaborating and engage with teams

About us

Skit (previously known as http://vernacular.ai/" target="_blank">Vernacular.ai) is an AI-first SaaS voice automation company. Its suite of speech and language solutions enable enterprises to automate their contact centre operations. With over 10 million hours of training data, its product - Vernacular Intelligent Voice Assistant (VIVA) can currently respond in 16+ languages, covering over 160+ dialects and replicating human-like conversations.

Skit currently serves a variety of enterprise clients across diverse sectors such as BFSI, F&B, Hospitality, Consumer Electronics and Travel & Tourism, including prominent clients like Axis Bank, Hathway, Porter and Barbeque Nation. It has been featured as one of the top-notch start-ups in the Cisco Launchpad’s Cohort 6 and is a part of the World Economic Forum’s Global Innovators Community. It has has also been listed in Forbes 30 Under 30 Asia start-ups 2021 for its remarkable industry innovation.

We are looking for ML Research Engineers to work on the following problems:

• Spoken Language Understanding and Dialog Management.
• Language semantics, parsing, and modeling across multiple languages.
• Speech Recognition, Speech Analytics and Voice Processing across multiple languages.
• Response Generation and Speech Synthesis.
• Active Learning, Monitoring and Observability mechanisms for deployments.

Responsibilities

• Design, build and evaluate Machine Learning solutions.
• Perform experiments and statistical analyses to draw conclusions and take modeling decisions.
• Study, implement and extend state of the art systems.
• Take part in regular research reviews and discussions.
• Build, maintain and extend our open source solutions in the domain.
• Write well-crafted programs at all levels of the system. This includes the data pipelines, experiment prototypes, fast and scalable deployment models, and evaluation, visualization and monitoring systems.

Requirements

• Practical Machine Learning experience as demonstrated by earlier works.
• Knowledge of and ability to use tools from theoretical and practical aspects of computer science. This includes, but is not limited to, probability, statistics, learning theory, algorithms, software architecture, programming languages, etc.
• Good programming skills and ability to work with programs at all levels of a finished Machine Learning product. We prefer language agnosticism since that exemplifies this point.
• Git portfolios and blogs are helpful as they let us better evaluate your work.

• What information we collect during our application and recruitment process and why we collect it;
• How we use that information; and
• How to access and update that information.

• Your name, address, email address, telephone number and other contact information;
• Your resume or CV, cover letter, previous and/or relevant work experience or other experience, education, transcripts, or other information you provide to us in support of an application and/or the application and recruitment process;
• Information from interviews and phone-screenings you may have, if any;
• Details of the type of employment you are or may be looking for, current and/or desired salary and other terms relating to compensation and benefits packages, willingness to relocate, or other job preferences;
• Details of how you heard about the position you are applying for;
• Reference information and/or information received from background checks (where applicable), including information provided by third parties;
• Information about your educational and professional background from publicly available sources, including online, that we believe is relevant to your application or a potential future application (e.g. your LinkedIn profile); and/or
• Information related to any assessment you may take as part of the interview screening process.

• Assessing your skills, qualifications and interests against our career opportunities;
• Verifying your information and carrying out reference checks and/or conducting background checks (where applicable) if you are offered a job;
• Communications with you about the recruitment process and/or your application(s), including, in appropriate cases, informing you of other potential career opportunities at Skit;
• Creating and/or submitting reports as required under any local laws and/or regulations, where applicable;
• Making improvements to Skit's application and/or recruitment process including improving diversity in recruitment practices;
• Proactively conducting research about your educational and professional background and skills and contacting you if we think you would be suitable for a role with us.

1. Proven experience with deploying and tuning Open Source components into enterprise ready production tooling Experience with datacentre (Metal as a Service – MAAS) and cloud deployment technologies (AWS or GCP Architect certificates required)
2. Deep understanding of Linux from kernel mechanisms through user space management
3. Experience on CI/CD (Continuous Integrations and Deployment) system solutions (Jenkins).
4. Using Monitoring tools (local and on public cloud platforms) Nagios, Prometheus, Sensu, ELK, Cloud Watch, Splunk, New Relic etc. to trigger instant alerts, reports and dashboards.  Work closely with the development and infrastructure teams to analyze and design solutions with four nines (99.99%) up-time, globally distributed, clustered, production and non-production virtualized infrastructure. 
5. Wide understanding of IP networking as well as data centre infrastructure

1. Expert with software development tools and sourcecode management, understanding, managing issues, code changes and grouping them into deployment releases in a stable and measurable way to maximize production Must be expert at developing and using ansible roles and configuring deployment templates with jinja2.
2. Solid understanding of data collection tools like Flume, Filebeat, Metricbeat, JMX Exporter agents.
3. Extensive experience operating and tuning the kafka streaming data platform, specifically as a message queue for big data processing
4. Strong understanding and must have experience:
5. Apache spark framework, specifically spark core and spark streaming, 
6. Orchestration platforms, mesos and kubernetes, 
7. Data storage platforms, elasticstack, carbon, clickhouse, cassandra, ceph, hdfs
8. Core presentation technologies kibana, and grafana.
9. Excellent scripting and programming skills (bash, python, java, go, rust). Must have previous experience with “rust” in order to support, improve in house developed products

Red Hat Certified Architect certificate or equivalent required CCNA certificate required 3-5 years of experience running open source big data platforms