Machine Learning Engineer

• Bring in industry best practices around creating and maintaining robust data pipelines for complex data projects with/without AI component
  • programmatically ingesting data from several static and real-time sources (incl. web scraping)
  • rendering results through dynamic interfaces incl. web / mobile / dashboard with the ability to log usage and granular user feedbacks
  • performance tuning and optimal implementation of complex Python scripts (using SPARK), SQL (using stored procedures, HIVE), and NoSQL queries in a production environment

• Industrialize ML / DL solutions and deploy and manage production services; proactively handle data issues arising on live apps
• Perform ETL on large and complex datasets for AI applications - work closely with data scientists on performance optimization of large-scale ML/DL model training
• Build data tools to facilitate fast data cleaning and statistical analysis
• Ensure data architecture is secure and compliant
• Resolve issues escalated from Business and Functional areas on data quality, accuracy, and availability
• Work closely with APAC CDO and coordinate with a fully decentralized team across different locations in APAC and global HQ (Paris).

•  Expert in structured and unstructured data in traditional and Big data environments – Oracle / SQLserver, MongoDB, Hive / Pig, BigQuery, and Spark
• Have excellent knowledge of Python programming both in traditional and distributed models (PySpark)
• Expert in shell scripting and writing schedulers
• Hands-on experience with Cloud - deploying complex data solutions in hybrid cloud / on-premise environment both for data extraction/storage and computation
• Hands-on experience in deploying production apps using large volumes of data with state-of-the-art technologies like Dockers, Kubernetes, and Kafka
• Strong knowledge of data security best practices
• 5+ years experience in a data engineering role
• Science / Engineering graduate from a Tier-1 university in the country
• And most importantly, you must be a passionate coder who really cares about building apps that can help people do things better, smarter, and faster even when they sleep

This profile will include the following responsibilities:

- Develop Parsers for XML and JSON Data sources/feeds

- Write Automation Scripts for product development

- Build API Integrations for 3^rd Party product integration

- Perform Data Analysis

- Research on Machine learning algorithms

- Understand AWS cloud architecture and work with 3 party vendors for deployments

About Company:

Working with a multitude of clients populating the FTSE and Fortune 500s, Audit Partnership is a people focused organization with a strong belief in our employees. We hire the best people to provide the best services to our clients.

APL offers profit recovery services to organizations of all sizes across a number of sectors. APL was borne out of a desire to offer an alternative from the stagnant service provision on offer in the profit recovery industry.

Every year we cover million of pounds for our clients and also work closely with them, sharing our audit findings to minimize future losses. Our dedicated and highly experienced audit teams utilize progressive & dynamic financial service solutions & industry leading technology to achieve maximum success.

We provide dynamic work environments focused on delivering data-driven solutions at a rapidly increased pace over traditional development. Be a part of our passionate and motivated team who are excited to use the latest in software technologies within financial services.

Headquartered in the UK, we have expanded from a small team in 2002 to a market leading organization serving clients across the globe while keeping our clients at the heart of all decisions we make.

Job description:

We are looking for a high-potential, enthusiastic SQL Data Engineer with a strong desire to build a career in data analysis, database design and application solutions. Reporting directly to our UK based Technology team, you will provide support to our global operation in the delivery of data analysis, conversion, and application development to our core audit functions.

Duties will include assisting with data loads, using T-SQL to analyse data, front-end code changes, data housekeeping, data administration, and supporting the Data Services team as a whole.  Your contribution will grow in line with your experience and skills, becoming increasingly involved in the core service functions and client delivery.  A self-starter with a deep commitment to the highest standards of quality and customer service. We are offering a fantastic career opportunity, working for a leading international financial services organisation, serving the world’s largest organisations.

What we are looking for:

• 1-2 years of previous experience in a similar role
• Data analysis and conversion skills using Microsoft SQL Server is essential
• An understanding of relational database design and build
• Schema design, normalising data, indexing, query performance analysis
• Ability to analyse complex data to identify patterns and detect anomalies
• Assisting with ETL design and implementation projects
• Knowledge or experience in one or more of the key technologies below would be preferable:
  • Microsoft SQL Server (SQL Server Management Studio, Stored Procedure writing etc)
  • T-SQL
  • Programming languages (C#, VB, Python etc)
  • Use of Python to manipulate and import data
  •  
  • Experience of ETL/automation advantageous but not essential (SSIS/Prefect/Azure)
• A self-starter who can drive projects with minimal guidance
• Meeting stakeholders to agree system requirements
• Someone who is enthusiastic and eager to learn
• Very good command of English and excellent communication skills

Perks & Benefits:

• A fantastic work life balance
• Competitive compensation and benefits
• Exposure of working with Fortune 500 organization
• Expert guidance and nurture from global leaders
• Opportunities for career and personal advancement with our continued global growth strategy
• Industry leading training programs
• A working environment that is exciting, fun and engaging

About Turing:

Turing enables U.S. companies to hire the world’s best remote software engineers. 100+ companies including those backed by Sequoia, Andreessen, Google Ventures, Benchmark, Founders Fund, Kleiner, Lightspeed, and Bessemer have hired Turing engineers. For more than 180,000 engineers across 140 countries, we are the preferred platform for finding remote U.S. software engineering roles. We offer a wide range of full-time remote opportunities for full-stack, backend, frontend, DevOps, mobile, and AI/ML engineers.

We are growing fast (our revenue 15x’d in the past 12 months and is accelerating), and we have raised $14M in seed funding (https://tcrn.ch/3lNKbM9">one of the largest in Silicon Valley) from:

• Facebook’s 1st CTO and Quora’s Co-Founder (Adam D’Angelo)
• Executives from Google, Facebook, Square, Amazon, and Twitter
• Foundation Capital (investors in Uber, Netflix, Chegg, Lending Club, etc.)
• Cyan Banister
• Founder of Upwork (Beerud Sheth)

We also raised a much larger round of funding in October 2020 that we will be publicly announcing over the coming month. 

Some articles about Turing:

• https://techcrunch.com/2020/08/25/turing-raises-14m-to-help-source-vet-place-and-manage-remote-developers-in-tech-jobs/">TechCrunch: Turing raises $14M seed to help source, vet, place, and manage remote developers
• https://www.theinformation.com/articles/six-startups-prospering-during-coronavirus">The Information: Six Startups Prospering During Coronavirus
• https://medium.com/@cyanbanister/turing-helps-the-world-level-up-ff44b4e6415d">Cyan Banister: Turing Helps the World Level Up
• https://turing.com/boundarylessblog/2019/10/the-future-of-work-is-remote/the-future-of-work/">Jonathan Siddharth (Turing CEO): The Future of Work is Remote.

Turing is led by successful repeat founders Jonathan Siddharth and Vijay Krishnan, whose last A.I. company leveraged elite remote talent and had a successful acquisition. (https://techcrunch.com/2017/02/23/revcontent-acquires-rover/">Techcrunch story). Turing’s leadership team is composed of ex-Engineering and Sales leadership from Facebook, Google, Uber, and Capgemini.

About the role:

Software developers from all over the world have taken 200,000+ tests and interviews on Turing. Turing has also recommended thousands of developers to its customers and got customer feedback in terms of customer interview pass/fail data and data from the success of the collaboration with a U.S customer. This generates a massive proprietary dataset with a rich feature set comprising resume and test/interview features and labels in the form of actual customer feedback. Continuing rapid growth in our business creates an ever-increasing data advantage for us. 

We are looking for a Machine Learning Scientist who can help solve a whole range of exciting and valuable machine learning problems at Turing. Turing collects a lot of valuable heterogeneous signals about software developers including their resume, GitHub profile and associated code and a lot of fine-grained signals from Turing’s own screening tests and interviews (that span various areas including Computer Science fundamentals, project ownership and collaboration, communication skills, proactivity and tech stack skills), their history of successful collaboration with different companies on Turing, etc. 

A machine learning scientist at Turing will help create deep developer profiles that are a good representation of a developer’s strengths and weaknesses as it relates to their probability of getting successfully matched to one of Turing’s partner companies and having a fruitful long-term collaboration. The ML scientist will build models that are able to rank developers for different jobs based on their probability of success at the job. 

     
 You will also help make Turing’s tests more efficient by assessing their ability to predict the probability of a successful match of a developer with at least one company. The prior probability of a registered developer getting matched with a customer is about 1%. We want our tests to adaptively reduce perplexity as steeply as possible and move this probability estimate rapidly toward either 0% or 100%; maximize expected information-gain per unit time in other words. 

As an ML Scientist on the team, you will have a unique opportunity to make an impact by advancing ML models and systems, as well as uncovering new opportunities to apply machine learning concepts to Turing product(s).

This role will directly report to Turing’s founder and CTO, https://www.linkedin.com/in/vijay0/">Vijay Krishnan. This is his https://scholar.google.com/citations?user=uCRc7DgAAAAJ&;hl=en">Google Scholar profile. 

Responsibilities:

• Enhance our existing machine learning systems using your core coding skills and ML knowledge.
• Take end to end ownership of machine learning systems - from data pipelines, feature engineering, candidate extraction, model training, as well as integration into our production systems.
• Utilize state-of-the-art ML modeling techniques to predict user interactions and the direct impact on the company’s top-line metrics.
• Design features and builds large scale recommendation systems to improve targeting and engagement.
• Identify new opportunities to apply machine learning to different parts of our product(s) to drive value for our customers.

Minimum Requirements:

• BS, MS, or Ph.D. in Computer Science or a relevant technical field (AI/ML preferred).
• Extensive experience building scalable machine learning systems and data-driven products working with cross-functional teams
• Expertise in machine learning fundamentals, applicable to search - Learning to Rank, Deep Learning, Tree-Based Models, Recommendation Systems, Relevance and Data mining, understanding of NLP approaches like W2V or Bert.
• 2+ years of experience applying machine learning methods in settings like recommender systems, search, user modeling, graph representation learning, natural language processing.
• Strong understanding of neural network/deep learning, feature engineering, feature selection, optimization algorithms. Proven ability to dig deep into practical problems and choose the right ML method to solve them.
• Strong programming skills in Python and fluency in data manipulation (SQL, Spark, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools.
• Good understanding of mathematical foundations of machine learning algorithms.
• Ability to be available for meetings and communication during Turing's "coordination hours" (Mon - Fri: 8 am to 12 pm PST).

Other Nice-to-have Requirements:

• First author publications in ICML, ICLR, NeurIPS, KDD, SIGIR, and related conferences/journals. 
• Strong performance in Kaggle competitions.
• 5+ years of industry experience or a Ph.D. with 3+ years of industry experience in applied machine learning in similar problems e.g. ranking, recommendation, ads, etc.
• Strong communication skills.
• Experienced in leading large-scale multi-engineering projects.
• Flexible, and a positive team player with outstanding interpersonal skills.

What you will be doing:

As a part of the Global Credit Risk and Data Analytics team, this person will be responsible for carrying out analytical initiatives which will be as follows: -

• Dive into the data and identify patterns
• Development of end-to-end Credit models and credit policy for our existing credit products
• Leverage alternate data to develop best-in-class underwriting models
• Working on Big Data to develop risk analytical solutions
• Development of Fraud models and fraud rule engine
• Collaborate with various stakeholders (e.g. tech, product) to understand and design best solutions which can be implemented
• Working on cutting-edge techniques e.g. machine learning and deep learning models

Example of projects done in past:

• Lazypay Credit Risk model using CatBoost modelling technique ; end-to-end pipeline for feature engineering and model deployment in production using Python
• Fraud model development, deployment and rules for EMEA region

Basic Requirements:

• 1-3 years of work experience as a Data scientist (in Credit domain)
• 2016 or 2017 batch from a premium college (e.g B.Tech. from IITs, NITs, Economics from DSE/ISI etc)
• Strong problem solving and understand and execute complex analysis
• Experience in at least one of the languages - R/Python/SAS and SQL
• Experience in in Credit industry (Fintech/bank)
• Familiarity with the best practices of Data Science

Add-on Skills : 

• Experience in working with big data
• Solid coding practices
• Passion for building new tools/algorithms
• Experience in developing Machine Learning models