Data Scientist

Job Description-

Responsibilities:

* Work on real-world computer vision problems

* Write robust industry-grade algorithms

* Leverage OpenCV, Python and deep learning frameworks to train models.

* Use Deep Learning technologies such as Keras, Tensorflow, PyTorch etc.

* Develop integrations with various in-house or external microservices.

* Must have experience in deployment practices (Kubernetes, Docker, containerization, etc.) and model compression practices

* Research latest technologies and develop proof of concepts (POCs).

* Build and train state-of-the-art deep learning models to solve Computer Vision related problems, including, but not limited to:

* Segmentation

* Object Detection

* Classification

* Objects Tracking

* Visual Style Transfer

* Generative Adversarial Networks

* Work alongside other researchers and engineers to develop and deploy solutions for challenging real-world problems in the area of Computer Vision

* Develop and plan Computer Vision research projects, in the terms of scope of work including formal definition of research objectives and outcomes

* Provide specialized technical / scientific research to support the organization on different projects for existing and new technologies

Skills:

* Object Detection

* Computer Science

* Image Processing

* Computer Vision

* Deep Learning

* Artificial Intelligence (AI)

* Pattern Recognition

* Machine Learning

* Data Science

* Generative Adversarial Networks (GANs)

* Flask

* SQL

About Slintel (a 6sense company) :

Slintel, a 6sense company,  the leader in capturing technographics-powered buying intent, helps companies uncover the 3% of active buyers in their target market. Slintel evaluates over 100 billion data points and analyzes factors such as buyer journeys, technology adoption patterns, and other digital footprints to deliver market & sales intelligence.

Slintel's customers have access to the buying patterns and contact information of more than 17 million companies and 250 million decision makers across the world.

Slintel is a fast growing B2B SaaS company in the sales and marketing tech space. We are funded by top tier VCs, and going after a billion dollar opportunity. At Slintel, we are building a sales development automation platform that can significantly improve outcomes for sales teams, while reducing the number of hours spent on research and outreach.

We are a big data company and perform deep analysis on technology buying patterns, buyer pain points to understand where buyers are in their journey. Over 100 billion data points are analyzed every week to derive recommendations on where companies should focus their marketing and sales efforts on. Third party intent signals are then clubbed with first party data from CRMs to derive meaningful recommendations on whom to target on any given day.

6sense is headquartered in San Francisco, CA and has 8 office locations across 4 countries.

6sense, an account engagement platform, secured $200 million in a Series E funding round, bringing its total valuation to $5.2 billion 10 months after its $125 million Series D round. The investment was co-led by Blue Owl and MSD Partners, among other new and existing investors.

Linkedin (Slintel) : https://www.linkedin.com/company/slintel/">https://www.linkedin.com/company/slintel/

Industry : Software Development

Company size : 51-200 employees (189 on LinkedIn)

Headquarters : Mountain View, California

Founded : 2016

Specialties : Technographics, lead intelligence, Sales Intelligence, Company Data, and Lead Data.

Website (Slintel) : https://www.slintel.com/slintel">https://www.slintel.com/slintel

Linkedin (6sense) : https://www.linkedin.com/company/6sense/">https://www.linkedin.com/company/6sense/

Industry : Software Development

Company size : 501-1,000 employees (937 on LinkedIn)

Headquarters : San Francisco, California

Founded : 2013

Specialties : Predictive intelligence, Predictive marketing, B2B marketing, and Predictive sales

Website (6sense) : https://6sense.com/">https://6sense.com/

Acquisition News : 

https://inc42.com/buzz/us-based-based-6sense-acquires-b2b-buyer-intelligence-startup-slintel/ 

Funding Details & News :

Slintel funding : https://www.crunchbase.com/organization/slintel">https://www.crunchbase.com/organization/slintel

6sense funding : https://www.crunchbase.com/organization/6sense">https://www.crunchbase.com/organization/6sense

https://www.nasdaq.com/articles/ai-software-firm-6sense-valued-at-%245.2-bln-after-softbank-joins-funding-round">https://www.nasdaq.com/articles/ai-software-firm-6sense-valued-at-%245.2-bln-after-softbank-joins-funding-round

https://www.bloomberg.com/news/articles/2022-01-20/6sense-reaches-5-2-billion-value-with-softbank-joining-round">https://www.bloomberg.com/news/articles/2022-01-20/6sense-reaches-5-2-billion-value-with-softbank-joining-round

https://xipometer.com/en/company/6sense">https://xipometer.com/en/company/6sense

Slintel & 6sense Customers :

https://www.featuredcustomers.com/vendor/slintel/customers

https://www.featuredcustomers.com/vendor/6sense/customers">https://www.featuredcustomers.com/vendor/6sense/customers

Responsibilities

• Work in collaboration with the application team and integration team to design, create, and maintain optimal data pipeline architecture and data structures for Data Lake/Data Warehouse
• Work with stakeholders including the Sales, Product, and Customer Support teams to assist with data-related technical issues and support their data analytics needs
• Assemble large, complex data sets from third-party vendors to meet business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimising data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Elastic search, MongoDB, and AWS technology
• Streamline existing and introduce enhanced reporting and analysis solutions that leverage complex data sources derived from multiple internal systems
  
  

Requirements

• 3+ years of experience in a Data Engineer role
• Proficiency in Linux
• Must have SQL knowledge and experience working with relational databases, query authoring (SQL) as well as familiarity with databases including Mysql, Mongo, Cassandra, and Athena
• Must have experience with Python/ Scala
• Must have experience with Big Data technologies like Apache Spark
• Must have experience with Apache Airflow
• Experience with data pipeline and ETL tools like AWS Glue
• Experience working with AWS cloud services: EC2 S3 RDS, Redshift and other Data solutions eg. Databricks, Snowflake

Python, SQL, Scala, Spark, ETL

Job Summary

As a Data Science Lead, you will manage multiple consulting projects of varying complexity and ensure on-time and on-budget delivery for clients. You will lead a team of data scientists and collaborate across cross-functional groups, while contributing to new business development, supporting strategic business decisions and maintaining & strengthening client base

1. Work with team to define business requirements, come up with analytical solution and deliver the solution with specific focus on Big Picture to drive robustness of the solution
2. Work with teams of smart collaborators. Be responsible for their appraisals and career development.
3. Participate and lead executive presentations with client leadership stakeholders.
4. Be part of an inclusive and open environment. A culture where making mistakes and learning from them is part of life
5. See how your work contributes to building an organization and be able to drive Org level initiatives that will challenge and grow your capabilities.

​​​​​​Role & Responsibilities

1. Serve as expert in Data Science, build framework to develop Production level DS/AI models.
2. Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients.
3. Lead multiple teams across clients ensuring quality and timely outcomes on all projects.
4. Lead and manage the onsite-offshore relation, at the same time adding value to the client.
5. Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions.
6. Build a winning team focused on client success. Help team members build lasting career in data science and create a constant learning/development environment.
7. Present results, insights, and recommendations to senior management with an emphasis on the business impact.
8. Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization.
9. Lead or contribute to org level initiatives to build the Tredence of tomorrow.

Qualification & Experience

1. Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Statistics, Data Science) or equivalent experience.
2. 6-10+ years of experience in data science, building hands-on ML models
3. Expertise in ML – Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning.
4. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA , Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers.
5. Knowledge of programming languages SQL, Python/ R, Spark.
6. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch).
7. Experience with cloud computing services (AWS, GCP or Azure)
8. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing
9. Knowledge in Mathematical programming – Linear Programming, Mixed Integer Programming etc , Stochastic Modelling – Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models.
10. Experience with Optimization Solvers (Gurobi, Cplex) and Algebraic programming Languages(PulP)
11. Knowledge in GPU code optimization, Spark MLlib Optimization.
12. Familiarity to deploy and monitor ML models in production, delivering data products to end-users.
13. Experience with ML CI/CD pipelines.

Specific Responsibilities

• Minimum of 2 years Experience in Google Big Query and Google Cloud Platform.
• Design and develop the ETL framework using BigQuery
• Expertise in Big Query concepts like Nested Queries, Clustering, Partitioning, etc.
• Working Experience of Clickstream database, Google Analytics/ Adobe Analytics.
• Should be able to automate the data load from Big Query using APIs or scripting language.
• Good experience in Advanced SQL concepts.
• Good experience with Adobe launch Web, Mobile & e-commerce tag implementation.
• Identify complex fuzzy problems, break them down in smaller parts, and implement creative, data-driven solutions
• Responsible for defining, analyzing, and communicating key metrics and business trends to the management teams
• Identify opportunities to improve conversion & user experience through data. Influence product & feature roadmaps.
• Must have a passion for data quality and be constantly looking to improve the system. Drive data-driven decision making through the stakeholders & drive Change Management
• Understand requirements to translate business problems & technical problems into analytics problems.
• Effective storyboarding and presentation of the solution to the client and leadership.
• Client engagement & management
• Ability to interface effectively with multiple levels of management and functional disciplines.
• Assist in developing/coaching individuals technically as well as on soft skills during the project and as part of Client Project’s training program.

• 2 to 3 years of working experience in Google Big Query & Google Cloud Platform
• Relevant experience in Consumer Tech/CPG/Retail industries
• Bachelor’s in engineering, Computer Science, Math, Statistics or related discipline
• Strong problem solving and web analytical skills. Acute attention to detail.
• Experience in analyzing large, complex, multi-dimensional data sets.
• Experience in one or more roles in an online eCommerce or online support environment.

• Expertise in Google Big Query & Google Cloud Platform
• Experience in Advanced SQL, Scripting language (Python/R)
• Hands-on experience in BI tools (Tableau, Power BI)
• Working Experience & understanding of Adobe Analytics or Google Analytics
• Experience in creating and debugging website & app tracking (Omnibus, Dataslayer, GA debugger, etc.)
• Excellent analytical thinking, analysis, and problem-solving skills.
• Knowledge of other GCP services is a plus

Responsibilities: 
 

• The Machine & Deep Machine Learning Software Engineer (Expertise in Computer Vision) will be an early member of a growing team with responsibilities for designing and developing highly scalable machine learning solutions that impact many areas of our business. 
• The individual in this role will help in the design and development of Neural Network (especially Convolution Neural Networks) & ML solutions based on our reference architecture which is underpinned by big data & cloud technology, micro-service architecture and high performing compute infrastructure. 
• Typical daily activities include contributing to all phases of algorithm development including ideation, prototyping, design, and development production implementation. 

Required Skills: 
 

• An ideal candidate will have a background in software engineering and data science with expertise in machine learning algorithms, statistical analysis tools, and distributed systems. 
• Experience in building machine learning applications, and broad knowledge of machine learning APIs, tools, and open-source libraries 
• Strong coding skills and fundamentals in data structures, predictive modeling, and big data concepts 
• Experience in designing full stack ML solutions in a distributed computing environment 
• Experience working with Python, Tensor Flow, Kera’s, Sci-kit, pandas, NumPy, AZURE, AWS GPU
• Excellent communication skills with multiple levels of the organization 
• Image CNN, Image processing, MRCNN, FRCNN experience is a must.

About Graphene  

Graphene is a Singapore Head quartered AI company which has been recognized as Singapore’s Best  

Start Up By Switzerland’s Seedstarsworld, and also been awarded as best AI platform for healthcare in Vivatech Paris. Graphene India is also a member of the exclusive NASSCOM Deeptech club. We are developing an AI plaform which is disrupting and replacing traditional Market Research with unbiased insights with a focus on healthcare, consumer goods and financial services.  

Graphene was founded by Corporate leaders from Microsoft and P&G, and works closely with the Singapore Government & Universities in creating cutting edge technology which is gaining traction with many Fortune 500 companies in India, Asia and USA.  

Graphene’s culture is grounded in delivering customer delight by recruiting high potential talent and providing an intense learning and collaborative atmosphere, with many ex-employees now hired by large companies across the world.  

Graphene has a 6-year track record of delivering financially sustainable growth and is one of the rare start-ups which is self-funded and is yet profitable and debt free. We have already created a strong bench strength of Singaporean leaders and are recruiting and grooming more talent with a focus on our US expansion.   

Job title: - Data Analyst 

Job Description  

Data Analyst responsible for storage, data enrichment, data transformation, data gathering based on data requests, testing and maintaining data pipelines. 

Responsibilities and Duties  

• Managing end to end data pipeline from data source to visualization layer 
• Ensure data integrity; Ability to pre-empt data errors 
• Organized managing and storage of data 
• Provide quality assurance of data, working with quality assurance analysts if necessary. 
• Commissioning and decommissioning of data sets. 

• Processing confidential data and information according to guidelines. 
• Helping develop reports and analysis. 
• Troubleshooting the reporting database environment and reports. 
• Managing and designing the reporting environment, including data sources, security, and metadata. 
• Supporting the data warehouse in identifying and revising reporting requirements. 

• Supporting initiatives for data integrity and normalization. 
• Evaluating changes and updates to source production systems. 
• Training end-users on new reports and dashboards. 
• Initiate data gathering based on data requirements 
• Analyse the raw data to check if the requirement is satisfied 

Qualifications and Skills   

• Technologies required: Python, SQL/ No-SQL database(CosmosDB)     
• Experience required 2 – 5 Years. Experience in Data Analysis using Python 

•  Understanding of software development life cycle   

• Plan, coordinate, develop, test and support data pipelines, document, support for reporting dashboards (PowerBI) 
• Automation steps needed to transform and enrich data.   
• Communicate issues, risks, and concerns proactively to management. Document the process thoroughly to allow peers to assist with support as needed.   
• Excellent verbal and written communication skills   

• Research and test novel machine learning approaches for analysing large-scale distributed computing applications.
• Develop production-ready implementations of proposed solutions across different models AI and ML algorithms, including testing on live customer data to improve accuracy,  efficacy, and robustness
• Work closely with other functional teams to integrate implemented systems into the SaaS platform
• Suggest innovative and creative concepts and ideas that would improve the overall platform

‍

The ideal candidate must have the following qualifications:

• 5 + years experience in practical implementation and deployment of large customer-facing ML based systems.
• MS or M Tech (preferred) in applied mathematics/statistics;  CS or Engineering disciplines are acceptable but must have with strong quantitative and applied mathematical skills
• In-depth working, beyond coursework, familiarity with classical and current ML techniques, both supervised and unsupervised learning techniques and algorithms
• Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimization
• Experience in working on modeling graph structures related to spatiotemporal systems
• Programming skills in Python is a must
• 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

Most importantly, you should be someone who is passionate about building new and innovative products that solve tough real-world problems.

Chennai, India