Sr. Data Science

We are a 20-year old IT Services company from Kolkata working in India and abroad. We primarily work as SSP(Software Solutions Partner) and serve some of the leading business houses in the country in various software project implementations specially on  SAP and Oracle platform and also working on Govt & Semi Govt projects as outsourcing partner all over PAN India.

Can be anywhere in India ( Mumbai ,Pune and Kolkata is

preferable)

JD

Machine Learning/Deep Learning experience above 3

years

• Clear and structured thinking and communication

Keywords: Machine Learning, Deep Learning, AI,

Regression, Classification, Clustering, NLP, CNN, RNN,

LSTM, AutoML, k-NN, Naive Bayes, SVM, Decision

Forests

• Understand granular requirement, underlying business

problem and convert to low level design

• Develop analytic process chain with pre-processing,

training, testing, boosting etc.

• Develop the technical deliverable in mcube

(Python/Spark ML/R, H2O/Tensorflow) as per design

• Ensure quality of deliverable (coding standards, data

quality, data reconciliation)

• Proactively reach out for risks to Technical Lead
• Machine Learning, Deep Learning, Regression,

Classification, Clustering, NLP,CNN, RNN

• Expertise in data analysis and analytic programming

(Python/R/ SparkML/Tensorflow)

• Experience in multiple data processing technology

(preferably Pentaho or Spark)

• Basic knowledge in effort estimation, Clear and

structured thinking and communication

• Expertise in testing accuracy of deliverables (model)
• Exposure to Data Modelling and Analysis
• Exposure to information delivery (model outcome

communication)

Qualification:

M.S. / M.Tech/ B.Tech / B.E. (in this order of preference)

• Masters course in Data Science after technical (engineering/

science) degree

Purpose of Job:
Responsible to lead a team of analysts to build and deploy predictive models to infuse core
business functions with deep analytical insights. The Senior Data Scientist will also work
closely with the Kinara management team to investigate strategically important business questions.

Job Responsibilities:

Lead a team through the entire analytical and machine learning model life cycle:
 Define the problem statement
 Build and clean datasets
 Exploratory data analysis
 Feature engineering
 Apply ML algorithms and assess the performance
 Code for deployment
 Code testing and troubleshooting
 Communicate Analysis to Stakeholders
 Manage Data Analysts and Data Scientists

Qualifications:
 Education: MS/MTech/Btech graduates or equivalent with a focus on data science and
quantitative fields (CS, Engineering, Mathematics, Economics)

 Work Experience: 5+ years in a professional role with 3+ years in ML/AI
Other Requirements: ⮚ Domain knowledge in Financial Services is a big plus

Skills & Competencies
Technical Skills
⮚ Aptitude in Math and Stats
⮚ Proven experience in the use of Python, SQL, DevOps
⮚ Excellent in programming (Python), stats tools, and SQL
⮚ Working knowledge of tools and utilities - AWS, Git, Selenium, Postman,Prefect, Airflow, PySpark

Soft Skills
⮚ Deep Curiosity and Humility
⮚ Strong communications verbal and written

Spotmentor is focussed on using the Intelligence-age tools and technologies like AI and Text analytics to create HR technology products which go beyond compliance and ERPs to give HR the power to become strategic, improve business results and increase the competitiveness. The HR and People departments have long sought to become strategic partners with businesses. We are focussed on taking this concept out of the board room meetings and making it a reality and you can be a part of this journey. At the end of it, you would be able to claim that there was an inflection point in History, which changed how business was transacted and you made that happen. Our first product is a Learning and Skill development platform which helps the organisations to acquire capabilities critical for them by helping employees attain their best potential through learning opportunities. Spotmentor was started by 4 IIT Kharagpur alumni with experiences in creating Technology products and Management consulting. We are looking for a Data Scientist who will help discover the information hidden in vast amounts of data, and help us make smarter decisions that benefit the employees of our customer organisations. Your primary focus will be on applying data mining techniques, doing statistical analysis, and building high quality prediction systems using structured and unstructured data. Technical Responsibilities: - Selecting features, building and optimizing classifiers using machine learning techniques - Data mining using state-of-the-art methods - Extending the existing data sets with third party sources of information - Processing, cleansing, and verifying the integrity of data used for analysis - Build recommendation systems - Automate scoring of documents using machine learning techniques Salary: This is a founding team member role with a salary of 20 Lacs to 30 Lacs per year and a meaningful ESOP component. Location: Gurgaon We believe in making Spotmentor the best place for the pursuit of excellence and diversity of opinions is an important tool to achieve that. Although as a startup our primary objective is growth, Spotmentor is focussed on creating a diverse and inclusive workplace where everyone can attain their best potential and we welcome female, minority and specially abled candidates to apply.

Job Responsibilities: 

 

• Identify valuable data sources and automate collection processes 
• Undertake preprocessing of structured and unstructured data. 
• Analyze large amounts of information to discover trends and patterns 
• Helping develop reports and analysis. 
• Present information using data visualization techniques. 

• Assessing tests and implementing new or upgraded software and assisting with strategic decisions on new systems. 
• Evaluating changes and updates to source production systems. 
• Develop, implement, and maintain leading-edge analytic systems, taking complicated problems and building simple frameworks 
• Providing technical expertise in data storage structures, data mining, and data cleansing. 
• Propose solutions and strategies to business challenges 

 

Desired Skills and Experience: 

 

• At least 1 year of experience in Data Analysis 
• Complete understanding of Operations Research, Data Modelling, ML, and AI concepts. 

• Knowledge of Python is mandatory, familiarity with MySQL, SQL, Scala, Java or C++ is an asset 
• Experience using visualization tools (e.g. Jupyter Notebook) and data frameworks (e.g. Hadoop) 
• Analytical mind and business acumen 
• Strong math skills (e.g. statistics, algebra) 
• Problem-solving aptitude 

• Excellent communication and presentation skills. 
• Bachelor’s / Master's Degree in Computer Science, Engineering, Data Science or other quantitative or relevant field is preferred  

Skill Set:

• 4+ years of experience Solid understanding of Python, Java and general software development skills (source code management, debugging, testing, deployment etc.).
• Experience in working with Solr and ElasticSearch Experience with NLP technologies & the handling of unstructured text Detailed understanding of text pre-processing and normalisation techniques such as tokenisation, lemmatisation, stemming, POS tagging etc.
• Prior experience in implementation of traditional ML solutions - classification, regression or clustering problem Expertise in text-analytics - Sentiment Analysis, Entity Extraction, Language modelling - and associated sequence learning models ( RNN, LSTM, GRU).
• Comfortable working with deep-learning libraries (eg. PyTorch)
• Candidate can even be a fresher with 1 or 2 years of experience IIIT, IIIT, Bits Pilani, top 5 local colleges are preferred colleges and universities.
• A Masters candidate in machine learning.
• Can source candidates from Mu Sigma and Manthan.

About Us

Censius is a US-based product company that is enabling AI at scale for enterprises. We are unlocking MLOps scalability by building the world's fastest way to deploy models and are amongst the earliest companies to tackle Model Performance Management. At Censius, you will get to solve difficult problems in a very nascent, but rapidly growing, area.

 

About the role

In this role, you will design and implement a generic ML platform that helps monitor models across modalities in production. You will collaborate with the research and development teams to build robust ML and big data monitoring platforms.

 

Responsibilities

* Work on large-scale machine learning challenges that impact millions of people around the globe

* Research and implement cutting-edge algorithms and implement pipelines that work with massive data sets in real-time

* Implementing fast, scalable solutions with optimal performance day in and out

* Machine-learning being the core of our business, this role will be responsible for all phases of the product development lifecycle

* Evaluate and validate the analyses with statistical methods and explain to people unfamiliar with the domain of data science

* Writing specifications for algorithms, reports on data analysis, documentation of algorithms, and collaborating with product teams' skills and attributes for success will want you to have

* Strong programming skills in Python.

* Working experience with a variety of ML techniques (decision trees, clustering, boosting, bagging, neural networks, etc.)

* Working experience with advanced statistical concepts (outliers, distance, regression, distributions, statistical tests, etc.)

* Hands-on experience with one or more machine learning frameworks - PyTorch, Keras, Tensorflow, XGBoost, and libraries - Pandas, NumPY, Scikit-learn

* Familiarity with ML platforms like MLflow, Weights&Biases, Kubeflow, and AWS SageMaker.It'd be nice if you have* Passion for developing data products from scratch and a high level of proactiveness

* Knowledge of Reinforcement learning and Optimisation problems on a large scale is a big plus

* Some experience in project management and mentoring is also a plus.

* Knowledge and experience in deploying large-scale systems using distributed and cloud-based systems (Hadoop, Amazon EC2) is a big plus.

 

You will excel in this role if

* You are scrappy, take ownership, and follow through to the very end

* You enjoy wearing multiple hats

* A sincere desire to learn and grow - we're quite small, so the desire to learn and grow as the company grows is essential!

 

Benefits

• Competitive Salary 💸
• Work Remotely 🌎
• Health insurance 🏥
• Unlimited Time Off ⏰
• Support for continual learning (free books and online courses) 📚
• Reimbursement for streaming services (think Netflix) 🎥
• Reimbursement for gym or physical activity of your choice 🏋🏽♀️
• Flex hours 💪
• Leveling Up Opportunities 🌱

About Vedantu --------------------------- If you have ever dreamed about being in the driver’s seat of a revolution, THIS is the place for you. Vedantu is an Ed-Tech startup which is into Live Online Tutoring. Recently raised Series B funding of $11M Job Description We are looking for a Data Scientist who will support our product, sales, leadership and marketing teams with insights gained from analyzing company data. The ideal candidate is adept at using large data sets to find opportunities for product, sales and process optimization and using models to test the effectiveness of different courses of action. They must have strong experience using a variety of data analysis methods, building and implementing models and using/creating appropriate algorithms. Desired Skills 1. Experience using statistical computer languages (R, Python,etc.) to manipulate data and draw insights from large data sets. 2. Process, cleanse, and verify the integrity of data used for analysis. 3. Comfortable manipulating and analyzing complex, high-volume, high-dimensionality data from varying, heterogeneous sources 4. Experience with messy real-world data -- handling missing/incomplete/inaccurate data 5. Understanding of a broad set of Algorithms and Applied Math. 6. Good at problem solving, probability and statistics and knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage) and experience with applications. 7. Knowledge of data scraping is preferable 8. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks) and their real-world advantages/drawbacks. 9. Experience with big data tools (Hadoop, Hive, MapReduce) a plus.

Work Location - Bangalore

 

The Data Analytics Senior Analyst is a seasoned professional role. Applies in-depth disciplinary knowledge, contributing to the development of new techniques and the improvement of processes and work-flow for the area or function. Integrates subject matter and industry expertise within a defined area. Requires in-depth understanding of how areas collectively integrate within the sub-function as well as coordinate and contribute to the objectives of the function and overall business. Evaluates moderately complex and variable issues with substantial potential impact, where development of an approach/taking of an action involves weighing various alternatives and balancing potentially conflicting situations using multiple sources of information. Requires good analytical skills in order to filter, prioritize and validate potentially complex and dynamic material from multiple sources. Strong communication and diplomacy skills are required. Regularly assumes informal/formal leadership role within teams. Involved in coaching and training of new recruits. Significant impact in terms of project size, geography, etc. by influencing decisions through advice, counsel and/or facilitating services to others in area of specialization. Work and performance of all teams in the area are directly affected by the performance of the individual.

Responsibilities:

• Build and enhance the software stack for modelling and data analytics
• Incorporate relevant data related algorithms in the products to solve business problems and improve them over time
• Automate repetitive data modelling and analytics tasks
• Keep up to date with available relevant technologies, to solve business problems
• Become a subject matter expert and closely work with analytics users to understand their need & provide recommendations/solutions
• Help define/share best practices for the business users and  enforce/monitor that best practices are being incorporated for better efficiency (speed to market & system performance)
• Share daily/weekly  progress made by the team
• Work with senior stakeholders & drive the discussions independently
• Mentor and lead a team of software developers on analytics related product development practices

Qualifications:

• 10-13 years of data engineering experience.
• Experience in working on machine-learning model deployment/scoring, model lifecycle management and model performance measurement.
• In-depth understanding of statistics and probability distributions, with experience of applying it in big-data software products for solving business problems
• Hands-on programming experience with big-data and analytics related product development using Python, Spark and Kafka to provide solutions for business needs.
• Intuitive with good interpersonal-skills, time-management and task-prioritization
• Ability to lead a technical team of software developers and mentor them on good software development practices.
• Ability to quickly grasp the business problem and nuances when put forth.
• Ability to quickly put together an execution plan and see it through till closure.
• Strong communication, presentation and influencing skills.

Education:

• Bachelor’s/University degree or equivalent experience
• Data Science or Analytics specialization preferred

 

 

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.

About us
DataWeave provides Retailers and Brands with “Competitive Intelligence as a Service” that enables them to take key decisions that impact their revenue. Powered by AI, we provide easily consumable and actionable competitive intelligence by aggregating and analyzing billions of publicly available data points on the Web to help businesses develop data-driven strategies and make smarter decisions.

Data Science@DataWeave
We the Data Science team at DataWeave (called Semantics internally) build the core machine learning backend and structured domain knowledge needed to deliver insights through our data products. Our underpinnings are: innovation, business awareness, long term thinking, and pushing the envelope. We are a fast paced labs within the org applying the latest research in Computer Vision, Natural Language Processing, and Deep Learning to hard problems in different domains.

How we work?
It's hard to tell what we love more, problems or solutions! Every day, we choose to address some of the hardest data problems that there are. We are in the business of making sense of messy public data on the web. At serious scale!

What do we offer?
- Some of the most challenging research problems in NLP and Computer Vision. Huge text and image datasets that you can play with!
- Ability to see the impact of your work and the value you're adding to our customers almost immediately.
- Opportunity to work on different problems and explore a wide variety of tools to figure out what really excites you.
- A culture of openness. Fun work environment. A flat hierarchy. Organization wide visibility. Flexible working hours.
- Learning opportunities with courses and tech conferences. Mentorship from seniors in the team.
- Last but not the least, competitive salary packages and fast paced growth opportunities.

Who are we looking for?
The ideal candidate is a strong software developer or a researcher with experience building and shipping production grade data science applications at scale. Such a candidate has keen interest in liaising with the business and product teams to understand a business problem, and translate that into a data science problem. You are also expected to develop capabilities that open up new business productization opportunities.

We are looking for someone with 6+ years of relevant experience working on problems in NLP or Computer Vision with a Master's degree (PhD preferred).

Key problem areas
- Preprocessing and feature extraction noisy and unstructured data -- both text as well as images.
- Keyphrase extraction, sequence labeling, entity relationship mining from texts in different domains.
- Document clustering, attribute tagging, data normalization, classification, summarization, sentiment analysis.
- Image based clustering and classification, segmentation, object detection, extracting text from images, generative models, recommender systems.
- Ensemble approaches for all the above problems using multiple text and image based techniques.

Relevant set of skills
- Have a strong grasp of concepts in computer science, probability and statistics, linear algebra, calculus, optimization, algorithms and complexity.
- Background in one or more of information retrieval, data mining, statistical techniques, natural language processing, and computer vision.
- Excellent coding skills on multiple programming languages with experience building production grade systems. Prior experience with Python is a bonus.
- Experience building and shipping machine learning models that solve real world engineering problems. Prior experience with deep learning is a bonus.
- Experience building robust clustering and classification models on unstructured data (text, images, etc). Experience working with Retail domain data is a bonus.
- Ability to process noisy and unstructured data to enrich it and extract meaningful relationships.
- Experience working with a variety of tools and libraries for machine learning and visualization, including numpy, matplotlib, scikit-learn, Keras, PyTorch, Tensorflow.
- Use the command line like a pro. Be proficient in Git and other essential software development tools.
- Working knowledge of large-scale computational models such as MapReduce and Spark is a bonus.
- Be a self-starter—someone who thrives in fast paced environments with minimal ‘management’.
- It's a huge bonus if you have some personal projects (including open source contributions) that you work on during your spare time. Show off some of your projects you have hosted on GitHub.

Role and responsibilities
- Understand the business problems we are solving. Build data science capability that align with our product strategy.
- Conduct research. Do experiments. Quickly build throw away prototypes to solve problems pertaining to the Retail domain.
- Build robust clustering and classification models in an iterative manner that can be used in production.
- Constantly think scale, think automation. Measure everything. Optimize proactively.
- Take end to end ownership of the projects you are working on. Work with minimal supervision.
- Help scale our delivery, customer success, and data quality teams with constant algorithmic improvements and automation.
- Take initiatives to build new capabilities. Develop business awareness. Explore productization opportunities.
- Be a tech thought leader. Add passion and vibrance to the team. Push the envelope. Be a mentor to junior members of the team.
- Stay on top of latest research in deep learning, NLP, Computer Vision, and other relevant areas.