Data Analyst(Python, ETL & SQL)
at Top Management Consulting Company
python, sql, etl (building etl pipelines)
EXPERIENCE : 3 -7 years of experience in Data Engineering or Data Warehousing
LOCATION: Bangalore and Gurugram
COMPANY DESCRIPTION:
- Bachelor’s degree in Engineering or Computer Science; Master’s degree is a plus
- 3+ years of professional work experience with a reputed analytics firm
- Expertise in handling large amount of data through Python
- Conduct data assessment, perform data quality checks and transform data using SQL and ETL tools
- Experience of deploying ETL / data pipelines and workflows in cloud techhnologies and architecture such as Azure and Amazon Web Services will be valued
- Comfort with data modelling principles (e.g. database structure, entity relationships, UID etc.)and software development principles (e.g. modularization, testing, refactoring, etc.)
- A thoughtful and comfortable communicator (verbal and written) with the ability to facilitate discussions and conduct training
- Track record of strong problemsolving, requirement gathering, and leading by example
- Ability to thrive in a flexible and collaborative environment
- Track record of completing projects successfully on time, within budget and as per scope
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Data Science Engineer
Enterprise minds is looking for Data Scientist.
Strong in Python,Pyspark.
Prefer immediate joiners
We are looking for a Machine Learning Engineer with experience in model deployments. Candidate will be responsible for deploying AI / Machine Learning applications for our manufacturing clients. We expect them to have strong programming skills, and background of deployment of ML models for time series data. They should have a sturdy growth mind set and a strong work ethic. Candidate will interact with the data science team to understand the models and scalability of solution.
Key responsibilities:
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Design and set-up of ML model deployment pipelines and architectures
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Evaluation of the deployed ML models and deployment pipelines
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Coordination with the data science, data infrastructure team and customer for proper deployment of the models
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Writing production-ready code following software development principles
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Testing deployment pipelines
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Technical documentation of the projects
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Dashboard preparation for showing the results from the deployed models
Your background:
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Educational Background: B.Tech/M.Tech/BE in STEM fields
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Machine Learning Algorithms
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Supervised, Unsupervised, Timeseries analysis, Time series Feature Engineering
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AI Deployment workflows
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ML Libraries: scikit-learn, pandas, numpy, matplotlib, seaborn, plotly
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Code and Data version control: Git, DVC, etc
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MLOPs: AI Workflow and Pipeline Orchestration Tools
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Docker
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Kubeflow, Airflow, etc
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AWS Sagemaker, GCP, or Azure
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Database management:
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SQL, Timestream DB, InfluxDB
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Visualization Dashboard Platforms
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Grafana, Tableau
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Misc. Tools and Protocols
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Familiarity with Linux based system
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Good to have ML Libraries:
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Pycaret, Pytorch, Tensorflow, TsFresh
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Desirable to have certifications in Data Science tools and methodologies.
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Strong written and verbal communication skills
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Excellent problem solving and data analytical skills
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The ability to drive culture changes in an organization.
Our Team Culture:
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Working for one of the technology leaders in Europe in one of the most innovative and promising industry sectors
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Short decision-making paths and the opportunity to contribute and implement your own ideas
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Positive, motivated, and energetic working atmosphere in a team with experienced Digitization experts and long-term entrepreneurs
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Option to also work from Home
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Steep learning curve and opportunities for personal and professional training and further education
Data Scientist (Risk)/Sr. Data Scientist (Risk)
As a part of the Data science/Analytics team at Rupifi, you will play a significant role in helping define the business/product vision and deliver it from the ground up by working with passionate high-performing individuals in a very fast-paced working environment.
You will work closely with Data Scientists & Analysts, Engineers, Designers, Product Managers, Ops Managers and Business Leaders, and help the team make informed data driven decisions and deliver high business impact.
Preferred Skills & Responsibilities:
- Analyze data to better understand potential risks, concerns and outcomes of decisions.
- Aggregate data from multiple sources to provide a comprehensive assessment.
- Past experience of working with business users to understand and define inputs for risk models.
- Ability to design and implement best in class Risk Models in Banking & Fintech domain.
- Ability to quickly understand changing market trends and incorporate them into model inputs.
- Expertise in statistical analysis and modeling.
- Ability to translate complex model outputs into understandable insights for business users.
- Collaborate with other team members to effectively analyze and present data.
- Conduct research into potential clients and understand the risks of accepting each one.
- Monitor internal and external data points that may affect the risk level of a decision.
Tech skills:
- Hands-on experience in Python & SQL.
- Hands-on experience in any visualization tool preferably Tableau
- Hands-on experience in Machine & Deep Learning area
- Experience in handling complex data sources
- Experience in modeling techniques in the fintech/banking domain
- Experience of working on Big data and distributed computing.
Preferred Qualifications:
- A BTech/BE/MSc degree in Math, Engineering, Statistics, Economics, ML, Operations Research, or similar quantitative field.
- 3 to 10 years of modeling experience in the fintech/banking domain in fields like collections, underwriting, customer management, etc.
- Strong analytical skills with good problem solving ability
- Strong presentation and communication skills
- Experience in working on advanced machine learning techniques
- Quantitative and analytical skills with a demonstrated ability to understand new analytical concepts.
The responsibilities of a tableau developer include creating technical solutions, creating data storage tools, and conducting tests. To be successful as a tableau developer, you should have a broad understanding of the business technology landscape, the ability to design reports, and strong analytical skills.
Senior Artificial intelligence/ Machine Learning Developer
at A firm which woks with US clients. Permanent WFH.
This person MUST have:
- B.E Computer Science or equivalent
- 5 years experience with the Django framework
- Experience with building APIs (REST or GraphQL)
- Strong Troubleshooting and debugging skills
- React.js knowledge would be an added bonus
- Understanding on how to use a database like Postgres (prefered choice), SQLite, MongoDB, MySQL.
- Sound knowledge of object-oriented design and analysis.
- A strong passion for writing simple, clean and efficient code.
- Proficient understanding of code versioning tools Git.
- Strong communication skills.
Experience:
- Min 5 year experience
- Startup experience is a must.
Location:
- Remote developer
Timings:
- 40 hours a week but with 4 hours a day overlapping with client timezone. Typically clients are in California PST Timezone.
Position:
- Full time/Direct
- We have great benefits such as PF, medical insurance, 12 annual company holidays, 12 PTO leaves per year, annual increments, Diwali bonus, spot bonuses and other incentives etc.
- We dont believe in locking in people with large notice periods. You will stay here because you love the company. We have only a 15 days notice period.
Data Scientist
at Credit Saison Finance Pvt Ltd
1) Understand the business objectives, formulate hypotheses and collect the relevant data using SQL/R/Python. Analyse bureau, customer and lending performance data on a periodic basis to generate insights. Present complex information and data in an uncomplicated, easyto-understand way to drive action.
2) Independently Build and refit robust models for achieving game-changing growth while managing risk.
3) Identify and implement new analytical/modelling techniques to improve model performance across customer lifecycle (acquisitions, management, fraud, collections, etc.
4) Help define the data infrastructure strategy for Indian subsidiary.
a. Monitor data quality and quantity.
b. Define a strategy for acquisition, storage, retention, and retrieval of data elements. e.g.: Identify new data types and collaborate with technology teams to capture them.
c. Build a culture of strong automation and monitoring
d. Staying connected to the Analytics industry trends - data, techniques, technology, etc. and leveraging them to continuously evolve data science standards at Credit Saison.
Required Skills & Qualifications:
1) 3+ years working in data science domains with experience in building risk models. Fintech/Financial analysis experience is required.
2) Expert level proficiency in Analytical tools and languages such as SQL, Python, R/SAS, VBA etc.
3) Experience with building models using common modelling techniques (Logistic and linear regressions, decision trees, etc.)
4) Strong familiarity with Tableau//Power BI/Qlik Sense or other data visualization tools
5) Tier 1 college graduate (IIT/IIM/NIT/BITs preferred).
6) Demonstrated autonomy, thought leadership, and learning agility.
Problem Statement-Solution
Only 10% of India speaks English and 90% speak over 25 languages and 1000s of dialects. The internet has largely been in English. A good part of India is now getting internet connectivity thanks to cheap smartphones and Jio. The non-English speaking internet users will balloon to about 600 million users out of the total 750 million internet users in India by 2020. This will make the vernacular segment one of the largest segments in the world - almost 2x the size of the US population. The vernacular segment has very few products that they can use on the internet.
One large human need is that of sharing thoughts and connecting with people of the same community on the basis of language and common interests. Twitter serves this need globally but the experience is mostly in English. There’s a large unaddressed need for these vernacular users to express themselves in their mother tongue and connect with others from their community. Koo is a solution to this problem.
About Koo
Koo was founded in March 2020, as a micro-blogging platform in both Indian languages and English, which gives a voice to the millions of Indians who communicate in Indian languages.
Currently available in Assamese, Bengali, English, Hindi, Kannada, Marathi, Tamil and Telugu, Koo enables people from across India to express themselves online in their mother tongues. In a country where under 10% of the population speaks English as a native language, Koo meets the need for a social media platform that can deliver an immersive language experience to an Indian user, thereby enabling them to connect and interact with each other. The recently introduced ‘Talk to Type’ enables users to leverage the voice assistant to share their thoughts without having to type. In August 2021, Koo crossed 10 million downloads, in just 16 months of launch.
Since June 2021, Koo is available in Nigeria.
Founding Team
Koo is founded by veteran internet entrepreneurs - Aprameya Radhakrishna (CEO, Taxiforsure) and Mayank Bidawatka (Co-founder, Goodbox & Coreteam, redBus).
Technology Team & Culture
The technology team comprises sharp coders, technology geeks and guys who have been entrepreneurs or are entrepreneurial and extremely passionate towards technology. Talent is coming from the likes of Google, Walmart, Redbus, Dailyhunt. Anyone being part of a technology team will have a lot to learn from their peers and mentors. Download our android app and take a look at what we’ve built. Technology stack compromises of a wide variety of cutting-edge technologies like Kotlin, Java 15, Reactive Programming, MongoDB, Cassandra, Kubernetes, AWS, NodeJS, Python, ReactJS, Redis, Aerospike, ML, Deep learning etc. We believe in giving a lot of independence and autonomy to ownership-driven individuals.
Technology skill sets required for a matching profile
- Work experience of 4 to 8 years in building large scale high user traffic consumer facing applications with desire to work in a fast paced startup.
- Development experience of real-time data analytics backend infrastructure on AWS
- Responsible for building data and analytical engineering solutions with standard e2e design & ELT patterns, implementing data compaction pipelines, data modelling and overseeing overall data quality.
- Responsible to enable access of data in AWS S3 storage layer and transformations in Data Warehouse
- Implement Data warehouse entities with common re-usable data model designs with automation and data quality capabilities.
- Integrate domain data knowledge into development of data requirements.
- Identify downstream implications of data loads/migration (e.g., data quality, regulatory)
Role : Sr Data Scientist / Tech Lead – Data Science
Number of positions : 8
Responsibilities
- Lead a team of data scientists, machine learning engineers and big data specialists
- Be the main point of contact for the customers
- Lead data mining and collection procedures
- Ensure data quality and integrity
- Interpret and analyze data problems
- Conceive, plan and prioritize data projects
- Build analytic systems and predictive models
- Test performance of data-driven products
- Visualize data and create reports
- Experiment with new models and techniques
- Align data projects with organizational goals
Requirements (please read carefully)
- Very strong in statistics fundamentals. Not all data is Big Data. The candidate should be able to derive statistical insights from very few data points if required, using traditional statistical methods.
- Msc-Statistics/ Phd.Statistics
- Education – no bar, but preferably from a Statistics academic background (eg MSc-Stats, MSc-Econometrics etc), given the first point
- Strong expertise in Python (any other statistical languages/tools like R, SAS, SPSS etc are just optional, but Python is absolutely essential). If the person is very strong in Python, but has almost nil knowledge in the other statistical tools, he/she will still be considered a good candidate for this role.
- Proven experience as a Data Scientist or similar role, for about 7-8 years
- Solid understanding of machine learning and AI concepts, especially wrt choice of apt candidate algorithms for a use case, and model evaluation.
- Good expertise in writing SQL queries (should not be dependent upon anyone else for pulling in data, joining them, data wrangling etc)
- Knowledge of data management and visualization techniques --- more from a Data Science perspective.
- Should be able to grasp business problems, ask the right questions to better understand the problem breadthwise /depthwise, design apt solutions, and explain that to the business stakeholders.
- Again, the last point above is extremely important --- should be able to identify solutions that can be explained to stakeholders, and furthermore, be able to present them in simple, direct language.
https://www.youtube.com/watch?v=3nUs4YxppNE&feature=emb_rel_end">https://www.youtube.com/watch?v=3nUs4YxppNE&feature=emb_rel_end
- Hands-on development/maintenance experience in Tableau: Developing, maintaining, and managing advanced reporting, analytics, dashboards and other BI solutions using Tableau
- Reviewing and improving existing Tableau dashboards and data models/ systems and collaborating with teams to integrate new systems
- Provide support and expertise to the business community to assist with better utilization of Tableau
- Understand business requirements, conduct analysis and recommend solution options for intelligent dashboards in Tableau
- Experience with Data Extraction, Transformation and Load (ETL) – knowledge of how to extract, transform and load data
- Execute SQL data queries across multiple data sources in support of business intelligence reporting needs. Format query results / reports in various ways
- Participates in QA testing, liaising with other project team members and being responsive to client's needs, all with an eye on details in a fast-paced environment
- Performing and documenting data analysis, data validation, and data mapping/design
Key Performance Indicators (Indicate how performance will be measured: indicators, activities…) |
KPIs will be outlined in detail in the goal sheet |
Ideal Background (State the minimum and desirable education and experience level) |
Education |
Minimum: Graduation, preferably in Science |
Experience requirement: |
· Minimum: 2-3 years’ relevant work experience in the field of reporting and data analytics using Tableau. · Tableau certifications would be preferred · Work experience in the regulated medical device / Pharmaceutical industry would be an added advantage, but not mandatory |
Languages: |
Minimum: English (written and spoken) |
Specific Professional Competencies: Indicate any other soft/technical/professional knowledge and skills requirements |
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