Data Engineer

• 3+ years experience in practical implementation and deployment of ML based systems preferred.
• BE/B Tech or M Tech (preferred) in CS/Engineering with strong mathematical/statistical background
• Strong mathematical and analytical skills, especially statistical and ML techniques, with familiarity with different supervised and unsupervised learning algorithms
• Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimisation
• Experience in working on modeling graph structures related to spatiotemporal systems
• Programming skills in Python
• Experience in developing and deploying on cloud (AWS or Google or Azure)
• Good verbal and written communication skills
• Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow

Job Description:

The data science team is responsible for solving business problems with complex data. Data complexity could be characterized in terms of volume, dimensionality and multiple touchpoints/sources. We understand the data, ask fundamental-first-principle questions, apply our analytical and machine learning skills to solve the problem in the best way possible. 

Our ideal candidate

The role would be a client facing one, hence good communication skills are a must. 

The candidate should have the ability to communicate complex models and analysis in a clear and precise manner. 

The candidate would be responsible for:

• Comprehending business problems properly - what to predict, how to build DV, what value addition he/she is bringing to the client, etc.
• Understanding and analyzing large, complex, multi-dimensional datasets and build features relevant for business
• Understanding the math behind algorithms and choosing one over another
• Understanding approaches like stacking, ensemble and applying them correctly to increase accuracy

Desired technical requirements

• Proficiency with Python and the ability to write production-ready codes. 
• Experience in pyspark, machine learning and deep learning
• Big data experience, e.g. familiarity with Spark, Hadoop, is highly preferred
• Familiarity with SQL or other databases.

What you need to have:

Work Experience : 0-2 years

Responsibilities :

- Design and implement mathematical models for fundamental valuation of securities. The person will need to understand latest research in quantitative finance and implement the same.

- Design, back-testing and implementation of high-frequency trading strategies on international exchanges. Work as part of the market-making team to determine the signals and trading strategies to go live with.

- Conduct performance attribution of live portfolios.

Required Skills :

- Strong candidates should have 0-2 years of work experience and successful track record in quantitative analysis preferably in the capital markets domain.

- Post-Graduate degree in statistics, finance, mathematics, engineering (Computer Science preferred) or other quantitative or computational disciplines

- Experience in using some or all of the following packages: R, MATLAB, SPSS, CART, C# .Net, Python

- Good written and oral communication skills.

- Strong experience working both independently and in a team-oriented collaborative environment.

- Entrepreneurial, self-motivated individual - high energy, high activity levels - passion for working with an innovative, small but rapidly growing company.

Senior Product Analyst

Pampers Start Up Team

India / Remote Working

Team Description

Our internal team focuses on App Development with data a growing area within the structure. We have a clear vision and strategy which is coupled up with App Development, Data, Testing, Solutions and Operations. The data team sits across the UK and India whilst other teams sit across Dubai, Lebanon, Karachi and various cities in India.

Role Description

In this role you will use a range of tools and technologies to primarily working on providing data design, data governance, reporting and analytics on the Pampers App.

This is a unique opportunity for an ambitious candidate to join a growing business where they will get exposure to a diverse set of assignments, can contribute fully to the growth of the business and where there are no limits to career progression and reward.

Responsibilities

● To be the Data Steward and drive governance having full understanding of all the data that flows through the Apps to all systems

● Work with the campaign team to do data fixes when issues with campaigns

● Investigate and troubleshoot issues with product and campaigns giving clear RCA and impact analysis

● Document data, create data dictionaries and be the “go to” person in understanding what data flows

● Build dashboards and reports using Amplitude, Power BI and present to the key stakeholders

● Carry out adhoc data investigations into issues with the app and present findings back querying data in BigQuery/SQL/CosmosDB

● Translate analytics into a clear powerpoint deck with actionable insights

● Write up clear documentation on processes

● Innovate with new processes or ways of providing analytics and reporting

● Help the data lead to find new ways of adding value

Requirements

● Bachelor’s degree and a minimum of 4+ years’ experience in an analytical role preferably working in product analytics with consumer app data

● Strong SQL Server and Power BI required

● You have experience with most or all of these tools – SQL Server, Python, Power BI, BigQuery.

● Understanding of mobile app data (Events, CTAs, Screen Views etc)

● Knowledge of data architecture and ETL

● Experience in analyzing customer behavior and providing insightful recommendations

● Self-starter, with a keen interest in technology and highly motivated towards success

● Must be proactive and be prepared to address meetings

● Must show initiative and desire to learn business subjects

● Able to work independently and provide updates to management

● Strong analytical and problem-solving capabilities with meticulous attention to detail

● Excellent problem-solving skills; proven teamwork and communication skills

● Experience working in a fast paced “start-up like” environment

Desirable

• Knowledge of mobile analytical tools (Segment, Amplitude, Adjust, Braze and Google Analytics)
• Knowledge of loyalty data

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.