Data Science
Machine Learning (ML)Hi,
We are hiring for Data Scientist for Bangalore.
Req Skills:
- NLP
- ML programming
- Spark
- Model Deployment
- Experience processing unstructured data and building NLP models
- Experience with big data tools pyspark
- Pipeline orchestration using Airflow and model deployment experience is preferred
Subodh Popalwar
Software Engineer, Memorres
About EnterpriseMinds
Enterprise Minds, with core focus on engineering products, automation and intelligence, partners customers on the trajectory towards increasing outcomes, relevance and growth.
Harnessing the power of Data and the forces that define AI, Machine Learning and Data Science, we believe in institutionalising go-to-market models and not just explore possibilities.
We believe in a customer-centric ethic without and people-centric paradigm within. With a strong sense of community, ownership and collaboration our people work in a spirit of co-creation, co-innovation and co-development to engineer next-generation software products with the help of accelerators.
Through Communities we connect and attract talent that shares skills and expertise. Through Innovation Labs and global design studios we deliver creative solutions.
We create vertical isolated pods which has narrow but deep focus. We also create horizontal pods to collaborate and deliver sustainable outcomes.
We follow Agile methodologies to fail fast and deliver scalable and modular solutions. We constantly self-asses and realign to work with each customer in the most impactful manner.
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Role: Head of Analytics
Location: Bangalore (Full time)
ABOUT QRATA:
Qrata matches top talent with global career opportunities from the world’s leading digital companies including some of the world’s fastest growing startups using Qrata’s talent marketplaces. To sign-up, please visit Qrata Talent Sign-Up
ABOUT THE COMPANY WE ARE HIRING FOR:
Our client is offering credit card solutions for banks and financial institutions. It provides services like credit card design and onboarding, credit card authorization, payment processing, collections and dispute resolutions, credit card fraud detection, and more. They serve in the B2B space in the FinTech market segments.
POSITION OVERVIEW
We are seeking an experienced individual for the role of Head of Analytics. As the Head of Analytics, you will be responsible for driving data-driven decision-making, implementing advanced analytics strategies, and providing valuable insights to optimize our credit card business operations, sales and marketing, risk management & customer experience. Your expertise in statistical analysis, predictive modeling, and data visualization will be instrumental in driving growth and enhancing the overall performance of our credit card business.
Responsibilities:
1. Develop and implement Analytics Strategy:
o Define the analytics roadmap for the credit card business, aligning it with overall
business objectives.
o Identify key performance indicators (KPIs) and metrics to track the performance
of the credit card business.
o Collaborate with senior management and cross-functional teams to prioritize and
execute analytics initiatives. 2. Lead Data Analysis and Insights:
o Conduct in-depth analysis of credit card data, customer behavior, and market trends to identify opportunities for business growth and risk mitigation.
o Develop predictive models and algorithms to assess credit risk, customer segmentation, acquisition, retention, and upsell opportunities.
o Generate actionable insights and recommendations based on data analysis to optimize credit card product offerings, pricing, and marketing strategies.
o Regularly present findings and recommendations to senior leadership, using data visualization techniques to effectively communicate complex information.
3. Drive Data Governance and Quality:
o Oversee data governance initiatives, ensuring data accuracy, consistency, and
integrity across relevant systems and platforms.
o Collaborate with IT teams to optimize data collection, integration, and storage
processes to support advanced analytics capabilities.
o Establish and enforce data privacy and security protocols to comply with
regulatory requirements.
4. Team Leadership and Collaboration:
o Build and manage a high-performing analytics team, fostering a culture of innovation, collaboration, and continuous learning.
o Provide guidance and mentorship to the team, promoting professional growth and development.
o Collaborate with stakeholders across departments, including Marketing, Risk Management, and Finance, to align analytics initiatives with business objectives.
5. Stay Updated on Industry Trends:
o Keep abreast of emerging trends, techniques, and technologies in analytics, credit
card business, and the financial industry.
o Leverage industry best practices to drive innovation and continuous improvement
in analytics methodologies and tools.
Qualifications:
Bachelor's or master’s degree in Technology, Mathematics, Statistics, Economics, Computer Science, or a related field.
Proven experience (7+ years) in leading analytics teams in the credit card industry.
Strong expertise in statistical analysis, predictive modelling, data mining, and segmentation techniques.
Proficiency in data manipulation and analysis using programming languages such as Python, R, or SQL.
Experience with analytics tools such as SAS, SPSS, or Tableau.
Excellent leadership and team management skills, with a track record of building and developing high-performing teams.
Strong knowledge of credit card business and understanding of credit card industry dynamics, including risk management, marketing, and customer lifecycle.
Exceptional communication and presentation skills, with the ability to effectively communicate complex information to a varied audience.
Job Sector: IT, Software
Job Type: Permanent
Location: Chennai
Experience: 10 - 20 Years
Salary: 12 – 40 LPA
Education: Any Graduate
Notice Period: Immediate
Key Skills: Python, Spark, AWS, SQL, PySpark
Contact at triple eight two zero nine four two double seven
Job Description:
Requirements
- Minimum 12 years experience
- In depth understanding and knowledge on distributed computing with spark.
- Deep understanding of Spark Architecture and internals
- Proven experience in data ingestion, data integration and data analytics with spark, preferably PySpark.
- Expertise in ETL processes, data warehousing and data lakes.
- Hands on with python for Big data and analytics.
- Hands on in agile scrum model is an added advantage.
- Knowledge on CI/CD and orchestration tools is desirable.
- AWS S3, Redshift, Lambda knowledge is preferred
Data Engineer JD:
- Designing, developing, constructing, installing, testing and maintaining the complete data management & processing systems.
- Building highly scalable, robust, fault-tolerant, & secure user data platform adhering to data protection laws.
- Taking care of the complete ETL (Extract, Transform & Load) process.
- Ensuring architecture is planned in such a way that it meets all the business requirements.
- Exploring new ways of using existing data, to provide more insights out of it.
- Proposing ways to improve data quality, reliability & efficiency of the whole system.
- Creating data models to reduce system complexity and hence increase efficiency & reduce cost.
- Introducing new data management tools & technologies into the existing system to make it more efficient.
- Setting up monitoring and alarming on data pipeline jobs to detect failures and anomalies
What do we expect from you?
- BS/MS in Computer Science or equivalent experience
- 5 years of recent experience in Big Data Engineering.
- Good experience in working with Hadoop and Big Data technologies like HDFS, Pig, Hive, Zookeeper, Storm, Spark, Airflow and NoSQL systems
- Excellent programming and debugging skills in Java or Python.
- Apache spark, python, hands on experience in deploying ML models
- Has worked on streaming and realtime pipelines
- Experience with Apache Kafka or has worked with any of Spark Streaming, Flume or Storm
Focus Area:
|
R1 |
Data structure & Algorithms |
|
R2 |
Problem solving + Coding |
|
R3 |
Design (LLD) |
Location: Chennai
Summary of the Position:
Job Purpose:
Genesys is the global omnichannel customer experience and contact center solution leader. With over 4,500 successful customers, our customer experience platform and solutions help companies engage effortlessly with their customers, across all touchpoints, channels and interactions to deliver differentiated customer journeys, while maximizing revenue and loyalty.
Genesys is embracing AI and Machine Learning in delivering AI-powered products like Predictive Routing, Chat bots, and Customer Journey management. The PS Data Scientist share a passion for AI & data working with global project teams and customers to extend data science services across Genesys solutions both on premise and in the cloud.
Join us and be a part of this journey as we write Customer Success stories with these products.
Location: (Chennai/Hyderabad/Bangalore)
WHAT YOU DO:
- Interface with business customers, gathering and understanding requirements
- Interface with customer and Genesys data science teams in discovery, extraction, loading, data transformation, and analysis of results
- Define and utilize data intuition process to cleanse and verify the integrity of customer & Genesys data to be used for analysis
- Implement, own, and improve data pipelines using best practices in data modeling, ETL/ELT processes
- Build, improve, and provide ongoing optimization of high quality models
- Work with PS & Engineering to deliver specific customer requirements and report back customer feedback, issues and feature requests. Continuous improvement in reporting, analysis, overall process.
- Visualize, present and demonstrate findings as required. Perform knowledge transfer to customer and internal teams.
- Communicate within the global community respecting cultural, language and time zone variations
- Demonstrate flexibility to adjust working hours to match customer and team interactions
ABOUT YOU:
- Bachelor’s / Master’s degree in quantitative field (e.g. Computer Science, Statistics, Engineering)
- 2-4 years of relevant experience in Data Science or Data Engineering
- 2+ years of hands-on experience performing statistical data analysis across large datasets writing highly optimized SQL queries and utilizing Python (NumPy, Pandas) or similar software (Primary)
- Expertise with major statistical & analytical software like (Python or R or SAS) - Primary
- Experience in Snowflake, Tableau, Elasticsearch, Kibana and real time analytics solution development will be major plus (Secondary)
- Should have the application development background of using any contact center product suites such as Genesys, Avaya, Cisco etc.
- Expertise with data modelling, data warehousing and ETL/ELT development
- Expertise with database solutions such as SQL, MongoDB, Redshift, Hadoop, Hive
- Proficiency with REST API, JSON, (AWS/AZURE/GCP) - Primary
- Experience in working and delivering projects independently. Ability to multi-task and context switch between projects and tasks
- Curiosity, passion, and drive for data queries, analysis, quality, models
- Excellent communication, initiative, and coordination skills with great attention to detail. Ability to explain and discuss complex topics with both experts and business leaders
How You Do It:
How You Think: Understands the business and takes a non-traditional approach to solving common problems. Willing to draw outside the lines and find new ways to make an impact on old problems.
How You Interact: Can easily build collaborative relationships that energize individuals, teams, and the company into action. You are a global thinker and can work across locations and time zones. You are an excellent communicator and listener, and can easily persuade to drive a vision and purpose.
How You Own It: You are a hands-on executor who can drive change and clearly communicate across all stakeholders.
How You Show Up:
Embodies Genesys core cultural values and pushes to create an authentic employee experience. You are the type of person who can succeed through ambiguity, bringing clarity where there is no roadmap, who can re-set when a change in direction is needed without getting derailed or frustrated. You are authentic and in still the trust in others.
About Us
Genesys ® powers more than 25 billion of the world’s best customer experiences each year. We put the customer at the center of everything we do and passionately believe that great customer engagement drives great business outcomes. More than 10,000 companies in more than 100 countries trust the industry’s #1 customer experience platform to orchestrate omnichannel customer journeys that eliminate silos and build lasting relationships. With a strong track record of innovation and a never-ending desire to be first, Genesys is the only company recognized by top industry analysts as a leader in both cloud and on-premise customer engagement solutions. Connect with Genesys via www.genesys.com , Twitter , Facebook , YouTube , LinkedIn , and the Genesys blog.
Genesys is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.
Machine Learning (ML)Data Science- Data & Analytics team is responsible to integrate new data sources and build data models, data dictionaries and machine learning models for the Wholesale Bank.
- The goal is to design and build data products to support squads in Wholesale Bank with business outcomes and development of business insights. In this Job Family we make a distinction between Data Analysts and Data Scientist. Both scientists as analysts work with data and are expected to write queries, work with engineering teams to source the right data, perform data munging (getting data into the correct format, convenient for analysis/interpretation) and derive information from data.
- The data analyst typically works on simpler structured SQL or similar databases or with other BI tools/packages. The Data Scientists are expected to build statistical models or be hands-on in machine learning and advanced programming.
- Role of Data Scientist to support our Corporate banking teams with insights gained from analyzing company data. The ideal candidate is adept at using large data sets to find opportunities for product 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 mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have banking or corporate banking experience.
6 Years - 10 Years
Analytics
- Should be comfortable in solving Wholesale Banking domain analytical solution within AI/ML platform
Data ScienceMachine Learning (ML)Proactively fetches information from various sources and analyzes it for a better understanding of how the business performs, and to build AI tools that automate certain processes within the company.
Roles & Responsibilities
- Develop novel computer vision/NLP algorithms
- Build large datasets that will be used to train the models
- Empirically evaluate related research works
- Train and evaluate deep learning architectures on multiple large scale datasets
- Collaborate with the rest of the research team to produce high quality research
- Manage a team of 2+ interns
Must-have skills
- 2+years of experience in building deep learning models
- Strong basics around probability and statistics, linear algebra, data structure & algorithms
- Good knowledge of classic ML algorithms (regression, SVM, PCA etc.), deep learning
- Strong programming skills
Nice to have skills
- Familiarity with pytorch
- Knowledge of SOTA techniques in NLP and Vision
Benefits
- High level of responsibility and ownership for a product impacting billions of lives.
- Extremely high-quality talent to work with. Work with a global team between US / India.
- Work from anywhere anytime!
- Best of breed industry benefits packages.
Data Science
R Programming
Python
Amazon Web Services (AWS)As an experienced Data Scientist you’ll join a team of data scientists, analysts, and software engineers
working to push the boundaries of data science in health care. We like to experiment, iterate, and
innovate with technology, from developing new algorithms specific to health care’s challenges, to
bringing the latest machine learning practices and applications developed in other industries into the
health care world. We know that algorithms are only valuable when powered by the right data, so we
focus on fully understanding the problems we need to solve, and truly understanding the data behind
them before launching into solutions – ensuring that the solutions we do land on are impactful and
powerful
Essential functions
• Research, conceptualize, and implement analytical approaches and predictive modeling to
evaluate scenarios, predict utilization and clinical outcomes, and recommend actions to impact
results.
• Manage and execute on the entire model development process, including scope definition,
hypothesis formation, data cleaning and preparation, feature selection, model implementation
in production, validation and iteration, using multiple data sources.
• Provide guidance on necessary data and software infrastructure capabilities to deliver a scalable
solution across partners and support the implementation of the team’s algorithms and models
• Contribute to the development and publication in major journals, conferences showcasing
leadership in healthcare data science.
• Work closely and collaborate with Data Scientists, Machine Learning engineers, IT teams and
Business stakeholders spread out across various locations in US and India to achieve business
goals
• Provide guidance to other Data Scientist and Machine Learning Engineers
Machine Learning (ML)
Deep Learning------------------------
Solve problems in speech and NLP domain using advanced Deep learning and Machine Learning techniques. Few examples of the problems are -
* Limited resource Speaker Diarization on mono-channel recordings in noisy environment.
* Speech Enhancement to improve accuracy of downstream speech analytics tasks.
* Automated Speech Recognition for accent heavy audio with a noisy background.
* Speech analytic tasks, which include: emotions, empathy, keyword extraction.
* Text analytic tasks, which include: topic modeling, entity and intent extraction, opinion mining, text classification, and sentiment detection on multilingual data.
A typical day at work
-----------------------------
You will work closely with the product team to own a business problem. You will then model the business problem into a Machine Learning problem. Next you will do literature review to identify approaches to solve the problem. Test these approaches, identify the best approach, add your own insights to improve the performance and ship that to production!
What should you know?
---------------------------------
* Solid understanding of Classical Machine Learning and Deep Learning concepts and algorithms.
* Experience with literature review either in academia or industry.
* Proficiency in at least one programming language such as Python, C, C++, Java, etc.
* Proficiency in Machine Learning tools such as TensorFlow, Keras, Caffe, Torch/PyTorch or Theano.
* Advanced degree in Computer Science, Electrical Engineering, Machine Learning, Mathematics, Statistics, Physics, or Computational Linguistics
Why DeepAffects?
--------------------------
* You’ll learn insanely fast here.
* Esops and competitive compensation.
* Opportunity and encouragement for publishing research at top conferences, paid trips to attend workshop and conferences where you have published.
* Independent work, flexible timings and sense of ownership of your work.
* Mentorship from distinguished researchers and professors.
Data SciencePythonMachine Learning (ML)Data ScienceMachine Learning (ML)Python
Follow CutshortSubodh Popalwar
Software Engineer, Memorres