About Spotmentor Technologies
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Data Scientist-
We are looking for an experienced Data Scientists to join our engineering team and
help us enhance our mobile application with data. In this role, we're looking for
people who are passionate about developing ML/AI in various domains that solves
enterprise problems. We are keen on hiring someone who loves working in fast paced start-up environment and looking to solve some challenging engineering
problems.
As one of the earliest members in engineering, you will have the flexibility to design
the models and architecture from ground up. As any early-stage start-up, we expect
you to be comfortable wearing various hats, and be proactive contributor in building
something truly remarkable.
Responsibilities
Researches, develops and maintains machine learning and statistical models for
business requirements
Work across the spectrum of statistical modelling including supervised,
unsupervised, & deep learning techniques to apply the right level of solution to
the right problem Coordinate with different functional teams to monitor outcomes and refine/
improve the machine learning models Implements models to uncover patterns and predictions creating business value and innovation
Identify unexplored data opportunities for the business to unlock and maximize
the potential of digital data within the organization
Develop NLP concepts and algorithms to classify and summarize structured/unstructured text data
Qualifications
3+ years of experience solving complex business problems using machine
learning.
Fluency in programming languages such as Python, NLP and Bert, is a must
Strong analytical and critical thinking skills
Experience in building production quality models using state-of-the-art technologies
Familiarity with databases like MySQL, Oracle, SQL Server, NoSQL, etc. is
desirable Ability to collaborate on projects and work independently when required.
Previous experience in Fintech/payments domain is a bonus
You should have Bachelor’s or Master’s degree in Computer Science, Statistics
or Mathematics or another quantitative field from a top tier Institute
Data Scientist – Delivery & New Frontiers Manager
Job Description:
We are seeking highly skilled and motivated data scientist to join our Data Science team. The successful candidate will play a pivotal role in our data-driven initiatives and be responsible for designing, developing, and deploying data science solutions that drives business values for stakeholders. This role involves mapping business problems to a formal data science solution, working with wide range of structured and unstructured data, architecture design, creating sophisticated models, setting up operations for the data science product with the support from MLOps team and facilitating business workshops. In a nutshell, this person will represent data science and provide expertise in the full project cycle. Expectation of the successful candidate will be above that of a typical data scientist. Beyond technical expertise, problem solving in complex set-up will be key to the success for this role.
Responsibilities:
- Collaborate with cross-functional teams, including software engineers, product managers, and business stakeholders, to understand business needs and identify data science opportunities.
- Map complex business problems to data science problem, design data science solution using GCP/Azure Databricks platform.
- Collect, clean, and preprocess large datasets from various internal and external sources.
- Streamlining data science process working with Data Engineering, and Technology teams.
- Managing multiple analytics projects within a Function to deliver end-to-end data science solutions, creation of insights and identify patterns.
- Develop and maintain data pipelines and infrastructure to support the data science projects
- Communicate findings and recommendations to stakeholders through data visualizations and presentations.
- Stay up to date with the latest data science trends and technologies, specifically for GCP companies
Education / Certifications:
Bachelor’s or Master’s in Computer Science, Engineering, Computational Statistics, Mathematics.
Job specific requirements:
- Brings 5+ years of deep data science experience
∙ Strong knowledge of machine learning and statistical modeling techniques in a in a clouds-based environment such as GCP, Azure, Amazon
- Experience with programming languages such as Python, R, Spark
- Experience with data visualization tools such as Tableau, Power BI, and D3.js
- Strong understanding of data structures, algorithms, and software design principles
- Experience with GCP platforms and services such as Big Query, Cloud ML Engine, and Cloud Storage
- Experience in configuring and setting up the version control on Code, Data, and Machine Learning Models using GitHub.
- Self-driven, be able to work with cross-functional teams in a fast-paced environment, adaptability to the changing business needs.
- Strong analytical and problem-solving skills
- Excellent verbal and written communication skills
- Working knowledge with application architecture, data security and compliance team.
- Own the product analytics of bidgely’s end user-facing products, measure and identify areas of improvement through data
- Liaise with Product Managers and Business Leaders to understand the product issues, priorities and hence support them through relevant product analytics
- Own the automation of product analytics through good SQL knowledge
- Develop early warning metrics for production and highlight issues and breakdowns for resolution
- Resolve client escalations and concerns regarding key business metrics
- Define and own execution
- Own the Energy Efficiency program designs, dashboard development, and monitoring of existing Energy efficiency program
- Deliver data-backed analysis and statistically proven solutions
- Research and implement best practices
- Mentor team of analysts
Qualifications and Education Requirements
- B.Tech from a premier institute with 5+ years analytics experience or Full-time MBA from a premier b-school with 3+ years of experience in analytics/business or product analytics
- Bachelor's degree in Business, Computer Science, Computer Information Systems, Engineering, Mathematics, or other business/analytical disciplines
Skills needed to excel
- Proven analytical and quantitative skills and an ability to use data and metrics to back up assumptions, develop business cases, and complete root cause
analyses - Excellent understanding of retention, churn, and acquisition of user base
- Ability to employ statistics and anomaly detection techniques for data-driven
analytics - Ability to put yourself in the shoes of the end customer and understand what
“product excellence” means - Ability to rethink existing products and use analytics to identify new features and product improvements.
- Ability to rethink existing processes and design new processes for more effective analyses
- Strong SQL knowledge, working experience with Looker and Tableau a great plus
- Strong commitment to quality visible in the thoroughness of analysis and techniques employed
- Strong project management and leadership skills
- Excellent communication (oral and written) and interpersonal skills and an ability to effectively communicate with both business and technical teams
- Ability to coach and mentor analysts on technical and analytical skills
- Good knowledge of statistics, basic machine learning, and AB Testing is
preferable - Experience as a Growth hacker and/or in Product analytics is a big plus
Designation – Deputy Manager - TS
Job Description
- Total of 8/9 years of development experience Data Engineering . B1/BII role
- Minimum of 4/5 years in AWS Data Integrations and should be very good on Data modelling skills.
- Should be very proficient in end to end AWS Data solution design, that not only includes strong data ingestion, integrations (both Data @ rest and Data in Motion) skills but also complete DevOps knowledge.
- Should have experience in delivering at least 4 Data Warehouse or Data Lake Solutions on AWS.
- Should be very strong experience on Glue, Lambda, Data Pipeline, Step functions, RDS, CloudFormation etc.
- Strong Python skill .
- Should be an expert in Cloud design principles, Performance tuning and cost modelling. AWS certifications will have an added advantage
- Should be a team player with Excellent communication and should be able to manage his work independently with minimal or no supervision.
- Life Science & Healthcare domain background will be a plus
Qualifications
BE/Btect/ME/MTech
Basic Qualifications:
- Five+ years experience working in a Big Data Software Development role
- Experience managing and deploying ML models in real world environments
- Bachelor's degree in Computer Science, Mathematics, Statistics, or other analytical fields
- Experience working with Python, Scala, Spark or other open-source software with data science libraries
- Experience in advanced math and statistics
- Excellent familiarity with command line linux environment
- Able to understand various data structures and common methods in data transformation
- Experience deploying machine learning models
2. hands on experience using python, sql, tablaue
3. Data Analyst
About Amagi & Growth
Amagi Corporation is a next-generation media technology company that provides cloud broadcast and targeted advertising solutions to broadcast TV and streaming TV platforms. Amagi enables content owners to launch, distribute and monetize live linear channels on Free-Ad-Supported TV and video services platforms. Amagi also offers 24x7 cloud managed services bringing simplicity, advanced automation, and transparency to the entire broadcast operations. Overall, Amagi supports 500+ channels on its platform for linear channel creation, distribution, and monetization with deployments in over 40 countries. Amagi has offices in New York (Corporate office), Los Angeles, and London, broadcast operations in New Delhi, and our Development & Innovation center in Bangalore. Amagi is also expanding in Singapore, Canada and other countries.
Amagi has seen phenomenal growth as a global organization over the last 3 years. Amagi has been a profitable firm for the last 2 years, and is now looking at investing in multiple new areas. Amagi has been backed by 4 investors - Emerald, Premji Invest, Nadathur and Mayfield. As of the fiscal year ending March 31, 2021, the company witnessed stellar growth in the areas of channel creation, distribution, and monetization, enabling customers to extend distribution and earn advertising dollars while saving up to 40% in cost of operations compared to traditional delivery models. Some key highlights of this include:
· Annual revenue growth of 136%
· 44% increase in customers
· 50+ Free Ad Supported Streaming TV (FAST) platform partnerships and 100+ platform partnerships globally
· 250+ channels added to its cloud platform taking the overall tally to more than 500
· Approximately 2 billion ad opportunities every month supporting OTT ad-insertion for 1000+ channels
· 60% increase in workforce in the US, UK, and India to support strong customer growth (current headcount being 360 full-time employees + Contractors)
· 5-10x growth in ad impressions among top customers
XressBees – a logistics company started in 2015 – is amongst the fastest growing companies of its sector. Our
vision to evolve into a strong full-service logistics organization reflects itself in the various lines of business like B2C
logistics 3PL, B2B Xpress, Hyperlocal and Cross border Logistics.
Our strong domain expertise and constant focus on innovation has helped us rapidly evolve as the most trusted
logistics partner of India. XB has progressively carved our way towards best-in-class technology platforms, an
extensive logistics network reach, and a seamless last mile management system.
While on this aggressive growth path, we seek to become the one-stop-shop for end-to-end logistics solutions. Our
big focus areas for the very near future include strengthening our presence as service providers of choice and
leveraging the power of technology to drive supply chain efficiencies.
Job Overview
XpressBees would enrich and scale its end-to-end logistics solutions at a high pace. This is a great opportunity to join
the team working on forming and delivering the operational strategy behind Artificial Intelligence / Machine Learning
and Data Engineering, leading projects and teams of AI Engineers collaborating with Data Scientists. In your role, you
will build high performance AI/ML solutions using groundbreaking AI/ML and BigData technologies. You will need to
understand business requirements and convert them to a solvable data science problem statement. You will be
involved in end to end AI/ML projects, starting from smaller scale POCs all the way to full scale ML pipelines in
production.
Seasoned AI/ML Engineers would own the implementation and productionzation of cutting-edge AI driven algorithmic
components for search, recommendation and insights to improve the efficiencies of the logistics supply chain and
serve the customer better.
You will apply innovative ML tools and concepts to deliver value to our teams and customers and make an impact to
the organization while solving challenging problems in the areas of AI, ML , Data Analytics and Computer Science.
Opportunities for application:
- Route Optimization
- Address / Geo-Coding Engine
- Anomaly detection, Computer Vision (e.g. loading / unloading)
- Fraud Detection (fake delivery attempts)
- Promise Recommendation Engine etc.
- Customer & Tech support solutions, e.g. chat bots.
- Breach detection / prediction
An Artificial Intelligence Engineer would apply himself/herself in the areas of -
- Deep Learning, NLP, Reinforcement Learning
- Machine Learning - Logistic Regression, Decision Trees, Random Forests, XGBoost, etc..
- Driving Optimization via LPs, MILPs, Stochastic Programs, and MDPs
- Operations Research, Supply Chain Optimization, and Data Analytics/Visualization
- Computer Vision and OCR technologies
The AI Engineering team enables internal teams to add AI capabilities to their Apps and Workflows easily via APIs
without needing to build AI expertise in each team – Decision Support, NLP, Computer Vision, for Public Clouds and
Enterprise in NLU, Vision and Conversational AI.Candidate is adept at working with 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 knowledge 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 be
comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion
for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
Roles & Responsibilities
● Develop scalable infrastructure, including microservices and backend, that automates training and
deployment of ML models.
● Building cloud services in Decision Support (Anomaly Detection, Time series forecasting, Fraud detection,
Risk prevention, Predictive analytics), computer vision, natural language processing (NLP) and speech that
work out of the box.
● Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
● Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively
communicating your needs and understanding theirs and address external and internal shareholder's
product challenges.
● Build core of Artificial Intelligence and AI Services such as Decision Support, Vision, Speech, Text, NLP, NLU,
and others.
● Leverage Cloud technology –AWS, GCP, Azure
● Experiment with ML models in Python using machine learning libraries (Pytorch, Tensorflow), Big Data,
Hadoop, HBase, Spark, etc
● Work with stakeholders throughout the organization to identify opportunities for leveraging company data to
drive business solutions.
● Mine and analyze data from company databases to drive optimization and improvement of product
development, marketing techniques and business strategies.
● Assess the effectiveness and accuracy of new data sources and data gathering techniques.
● Develop custom data models and algorithms to apply to data sets.
● Use predictive modeling to increase and optimize customer experiences, supply chain metric and other
business outcomes.
● Develop company A/B testing framework and test model quality.
● Coordinate with different functional teams to implement models and monitor outcomes.
● Develop processes and tools to monitor and analyze model performance and data accuracy.
● Develop scalable infrastructure, including microservices and backend, that automates training and
deployment of ML models.
● Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
● Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively
communicating your needs and understanding theirs and address external and internal shareholder's
product challenges.
● Deliver machine learning and data science projects with data science techniques and associated libraries
such as AI/ ML or equivalent NLP (Natural Language Processing) packages. Such techniques include a good
to phenomenal understanding of statistical models, probabilistic algorithms, classification, clustering, deep
learning or related approaches as it applies to financial applications.
● The role will encourage you to learn a wide array of capabilities, toolsets and architectural patterns for
successful delivery.
What is required of you?
You will get an opportunity to build and operate a suite of massive scale, integrated data/ML platforms in a broadly
distributed, multi-tenant cloud environment.
● B.S., M.S., or Ph.D. in Computer Science, Computer Engineering
● Coding knowledge and experience with several languages: C, C++, Java,JavaScript, etc.
● Experience with building high-performance, resilient, scalable, and well-engineered systems
● Experience in CI/CD and development best practices, instrumentation, logging systems
● Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights
from large data sets.
● Experience working with and creating data architectures.
● Good understanding of various machine learning and natural language processing technologies, such as
classification, information retrieval, clustering, knowledge graph, semi-supervised learning and ranking.
● Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest,
Boosting, Trees, text mining, social network analysis, etc.
● Knowledge on using web services: Redshift, S3, Spark, Digital Ocean, etc.
● Knowledge on creating and using advanced machine learning algorithms and statistics: regression,
simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
● Knowledge on analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Core metrics,
AdWords, Crimson Hexagon, Facebook Insights, etc.
● Knowledge on distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, Kafka etc.
● Knowledge on visualizing/presenting data for stakeholders using: Quicksight, Periscope, Business Objects,
D3, ggplot, Tableau etc.
● Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural
networks, etc.) and their real-world advantages/drawbacks.
● Knowledge of advanced statistical techniques and concepts (regression, properties of distributions,
statistical tests, and proper usage, etc.) and experience with applications.
● Experience building data pipelines that prep data for Machine learning and complete feedback loops.
● Knowledge of Machine Learning lifecycle and experience working with data scientists
● Experience with Relational databases and NoSQL databases
● Experience with workflow scheduling / orchestration such as Airflow or Oozie
● Working knowledge of current techniques and approaches in machine learning and statistical or
mathematical models
● Strong Data Engineering & ETL skills to build scalable data pipelines. Exposure to data streaming stack (e.g.
Kafka)
● Relevant experience in fine tuning and optimizing ML (especially Deep Learning) models to bring down
serving latency.
● Exposure to ML model productionzation stack (e.g. MLFlow, Docker)
● Excellent exploratory data analysis skills to slice & dice data at scale using SQL in Redshift/BigQuery.
About LodgIQ
LodgIQ is led by a team of experienced hospitality technology experts, data scientists and product domain experts. Seed funded by Highgate Ventures, a venture capital platform focused on early stage technology investments in the hospitality industry and Trilantic Capital Partners, a global private equity firm, LodgIQ has made a significant investment in advanced machine learning platforms and data science.
Title : Data Scientist
Job Description:
- Apply Data Science and Machine Learning to a REAL-LIFE problem - “Predict Guest Arrivals and Determine Best Prices for Hotels”
- Apply advanced analytics in a BIG Data Environment – AWS, MongoDB, SKLearn
- Help scale up the product in a global offering across 100+ global markets
Qualifications:
- Minimum 3 years of experience with advanced data analytic techniques, including data mining, machine learning, statistical analysis, and optimization. Student projects are acceptable.
- At least 1 year of experience with Python / Numpy / Pandas / Scipy/ MatPlotLib / Scikit-Learn
- Experience in working with massive data sets, including structured and unstructured with at least 1 prior engagement involving data gathering, data cleaning, data mining, and data visualization
- Solid grasp over optimization techniques
- Master's or PhD degree in Business Analytics. Data science, Statistics or Mathematics
- Ability to show a track record of solving large, complex problems
Responsibilities
- Understanding the business requirements so as to formulate the problems to solve and restrict the slice of data to be explored.
- Collecting data from various sources.
- Performing cleansing, processing, and validation on the data subject to analyze, in order to ensure its quality.
- Exploring and visualizing data.
- Performing statistical analysis and experiments to derive business insights.
- Clearly communicating the findings from the analysis to turn information into something actionable through reports, dashboards, and/or presentations.
Skills
- Experience solving problems in the project’s business domain.
- Experience with data integration from multiple sources
- Proficiency in at least one query language, especially SQL.
- Working experience with NoSQL databases, such as MongoDB and Elasticsearch.
- Working experience with popular statistical and machine learning techniques, such as clustering, linear regression, KNN, decision trees, etc.
- Good scripting skills using Python, R or any other relevant language
- Proficiency in at least one data visualization tool, such as Matplotlib, Plotly, D3.js, ggplot, etc.
- Great communication skills.