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- Conducting advanced statistical analysis to provide actionable insights, identify trends, and measure performance
- Performing data exploration, cleaning, preparation and feature engineering; in addition to executing tasks such as building a POC, validation/ AB testing
- Collaborating with data engineers & architects to implement and deploy scalable solutions
- Communicating results to diverse audiences with effective writing and visualizations
- Identifying and executing on high impact projects, triage external requests, and ensure timely completion for the results to be useful
- Providing thought leadership by researching best practices, conducting experiments, and collaborating with industry leaders
What you need to have:
- 2-4 year experience in machine learning algorithms, predictive analytics, demand forecasting in real-world projects
- Strong statistical background in descriptive and inferential statistics, regression, forecasting techniques.
- Strong Programming background in Python (including packages like Tensorflow), R, D3.js , Tableau, Spark, SQL, MongoDB.
- Preferred exposure to Optimization & Meta-heuristic algorithm and related applications
- Background in a highly quantitative field like Data Science, Computer Science, Statistics, Applied Mathematics,Operations Research, Industrial Engineering, or similar fields.
- Should have 2-4 years of experience in Data Science algorithm design and implementation, data analysis in different applied problems.
- DS Mandatory skills : Python, R, SQL, Deep learning, predictive analysis, applied statistics
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Our client combines Adtech and Martech platform strategy with data science & data engineering expertise, helping our clients make advertising work better for people.
- Act as primary day-to-day contact on analytics to agency-client leads
- Develop bespoke analytics proposals for presentation to agencies & clients, for delivery within the teams
- Ensure delivery of projects and services across the analytics team meets our stakeholder requirements (time, quality, cost)
- Hands on platforms to perform data pre-processing that involves data transformation as well as data cleaning
- Ensure data quality and integrity
- Interpret and analyse data problems
- Build analytic systems and predictive models
- Increasing the performance and accuracy of machine learning algorithms through fine-tuning and further
- Visualize data and create reports
- Experiment with new models and techniques
- Align data projects with organizational goals
Requirements
- Min 6 - 7 years’ experience working in Data Science
- Prior experience as a Data Scientist within a digital media is desirable
- Solid understanding of machine learning
- A degree in a quantitative field (e.g. economics, computer science, mathematics, statistics, engineering, physics, etc.)
- Experience with SQL/ Big Query/GMP tech stack / Clean rooms such as ADH
- A knack for statistical analysis and predictive modelling
- Good knowledge of R, Python
- Experience with SQL, MYSQL, PostgreSQL databases
- Knowledge of data management and visualization techniques
- Hands-on experience on BI/Visual Analytics Tools like PowerBI or Tableau or Data Studio
- Evidence of technical comfort and good understanding of internet functionality desirable
- Analytical pedigree - evidence of having approached problems from a mathematical perspective and working through to a solution in a logical way
- Proactive and results-oriented
- A positive, can-do attitude with a thirst to continually learn new things
- An ability to work independently and collaboratively with a wide range of teams
- Excellent communication skills, both written and oral
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- Minimum 2.5 years of experience as a Python Developer.
- Minimum 2.5 years of experience in any framework like Django/Flask/Fast API
- Minimum 2.5 years of experience in SQL/ Postgress
- Minimum 2.5 years of experience in Git/Gitlab/Bit-Bucket
- Minimum 2+ years of experience in deployment (CICD with Jenkins)
- Minimum 2.5 years of experience in any cloud like AWS/GCP/Azure
About Quadratyx:
We are a product-centric insight & automation services company globally. We help the world’s organizations make better & faster decisions using the power of insight & intelligent automation. We build and operationalize their next-gen strategy, through Big Data, Artificial Intelligence, Machine Learning, Unstructured Data Processing and Advanced Analytics. Quadratyx can boast more extensive experience in data sciences & analytics than most other companies in India.
We firmly believe in Excellence Everywhere.
Job Description
Purpose of the Job/ Role:
• As a Technical Lead, your work is a combination of hands-on contribution, customer engagement and technical team management. Overall, you’ll design, architect, deploy and maintain big data solutions.
Key Requisites:
• Expertise in Data structures and algorithms.
• Technical management across the full life cycle of big data (Hadoop) projects from requirement gathering and analysis to platform selection, design of the architecture and deployment.
• Scaling of cloud-based infrastructure.
• Collaborating with business consultants, data scientists, engineers and developers to develop data solutions.
• Led and mentored a team of data engineers.
• Hands-on experience in test-driven development (TDD).
• Expertise in No SQL like Mongo, Cassandra etc, preferred Mongo and strong knowledge of relational databases.
• Good knowledge of Kafka and Spark Streaming internal architecture.
• Good knowledge of any Application Servers.
• Extensive knowledge of big data platforms like Hadoop; Hortonworks etc.
• Knowledge of data ingestion and integration on cloud services such as AWS; Google Cloud; Azure etc.
Skills/ Competencies Required
Technical Skills
• Strong expertise (9 or more out of 10) in at least one modern programming language, like Python, or Java.
• Clear end-to-end experience in designing, programming, and implementing large software systems.
• Passion and analytical abilities to solve complex problems Soft Skills.
• Always speaking your mind freely.
• Communicating ideas clearly in talking and writing, integrity to never copy or plagiarize intellectual property of others.
• Exercising discretion and independent judgment where needed in performing duties; not needing micro-management, maintaining high professional standards.
Academic Qualifications & Experience Required
Required Educational Qualification & Relevant Experience
• Bachelor’s or Master’s in Computer Science, Computer Engineering, or related discipline from a well-known institute.
• Minimum 7 - 10 years of work experience as a developer in an IT organization (preferably Analytics / Big Data/ Data Science / AI background.
- Design the architecture of our big data platform
- Perform and oversee tasks such as writing scripts, calling APIs, web scraping, and writing SQL queries
- Design and implement data stores that support the scalable processing and storage of our high-frequency data
- Maintain our data pipeline
- Customize and oversee integration tools, warehouses, databases, and analytical systems
- Configure and provide availability for data-access tools used by all data scientists
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GREETINGS FROM CODEMANTRA !!!
EXCELLENT OPPORTUNITY FOR DATA SCIENCE/AI AND ML ARCHITECT !!!
Skills and Qualifications
*Strong Hands-on experience in Python Programming
*** Working experience with Computer Vision models - Object Detection Model, Image Classification
* Good experience in feature extraction, feature selection techniques and transfer learning
* Working Experience in building deep learning NLP Models for text classification, image analytics-CNN,RNN,LSTM.
* Working Experience in any of the AWS/GCP cloud platforms, exposure in fetching data from various sources.
* Good experience in exploratory data analysis, data visualisation, and other data pre-processing techniques.
* Knowledge in any one of the DL frameworks like Tensorflow, Pytorch, Keras, Caffe Good knowledge in statistics, distribution of data and in supervised and unsupervised machine learning algorithms.
* Exposure to OpenCV Familiarity with GPUs + CUDA Experience with NVIDIA software for cluster management and provisioning such as nvsm, dcgm and DeepOps.
* We are looking for a candidate with 9+ years of relevant experience , who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools: *Experience with big data tools: Hadoop, Spark, Kafka, etc.
*Experience with AWS cloud services: EC2, RDS, AWS-Sagemaker(Added advantage)
*Experience with object-oriented/object function scripting languages in any: Python, Java, C++, Scala, etc.
Responsibilities
*Selecting features, building and optimizing classifiers using machine learning techniques
*Data mining using state-of-the-art methods
*Enhancing data collection procedures to include information that is relevant for building analytic systems
*Processing, cleansing, and verifying the integrity of data used for analysis
*Creating automated anomaly detection systems and constant tracking of its performance
*Assemble large, complex data sets that meet functional / non-functional business requirements.
*Secure and manage when needed GPU cluster resources for events
*Write comprehensive internal feedback reports and find opportunities for improvements
*Manage GPU instances/machines to increase the performance and efficiency of the ML/DL model
Regards
Ranjith PR![skill icon](/_next/image?url=https%3A%2F%2Fcdn.cutshort.io%2Fpublic%2Fimages%2Fskill_icons%2Fpython.png&w=32&q=75)
Indium Software is a niche technology solutions company with deep expertise in Digital , QA and Gaming. Indium helps customers in their Digital Transformation journey through a gamut of solutions that enhance business value.
With over 1000+ associates globally, Indium operates through offices in the US, UK and India
Visit http://www.indiumsoftware.com">www.indiumsoftware.com to know more.
Job Title: Analytics Data Engineer
What will you do:
The Data Engineer must be an expert in SQL development further providing support to the Data and Analytics in database design, data flow and analysis activities. The position of the Data Engineer also plays a key role in the development and deployment of innovative big data platforms for advanced analytics and data processing. The Data Engineer defines and builds the data pipelines that will enable faster, better, data-informed decision-making within the business.
We ask:
Extensive Experience with SQL and strong ability to process and analyse complex data
The candidate should also have an ability to design, build, and maintain the business’s ETL pipeline and data warehouse The candidate will also demonstrate expertise in data modelling and query performance tuning on SQL Server
Proficiency with analytics experience, especially funnel analysis, and have worked on analytical tools like Mixpanel, Amplitude, Thoughtspot, Google Analytics, and similar tools.
Should work on tools and frameworks required for building efficient and scalable data pipelines
Excellent at communicating and articulating ideas and an ability to influence others as well as drive towards a better solution continuously.
Experience working in python, Hive queries, spark, pysaprk, sparkSQL, presto
- Relate Metrics to product
- Programmatic Thinking
- Edge cases
- Good Communication
- Product functionality understanding
Perks & Benefits:
A dynamic, creative & intelligent team they will make you love being at work.
Autonomous and hands-on role to make an impact you will be joining at an exciting time of growth!
Flexible work hours and Attractive pay package and perks
An inclusive work environment that lets you work in the way that works best for you!
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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.
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