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Using automated tools to extract data from primary and secondary sources
Removing corrupted data and fixing coding errors and related problems
Developing and maintaining databases, data systems – reorganizing data in a
readable format
Performing analysis to assess quality and meaning of data
Using statistical tools to identify, analyse, and interpret patterns and trends in
complex data sets that could be helpful for the diagnosis and prediction
Data analysis support to essential business functions so that business performance
can be assessed and compared over periods of time by creating essential business
dashboards
Preparing reports for the management stating trends, patterns, and predictions
using relevant data and generating meaningful insights from the data to support
business decision making
Working with programmers, engineers, and management heads to identify process
improvement opportunities, propose system modifications, and devise data
governance strategies
Preparing final analysis reports for the stakeholders to understand the data-analysis
steps, enabling them to take important decisions based on various facts and trends.
Skills Required
A successful analytics lead needs to have a combination of technical, management as
well leadership skills
A background in Mathematics, Statistics, Computer Science, Information
Management, or Economics can serve as a solid foundation to build your career in
analytics
Bachelor’s degree required, post-graduation is preferred with 5+ years of experience
in analytics field
Knowledge of programming languages like SQL, Oracle, R, MATLAB, and Python
Comfort with management data reporting tools like MS Excel, Google sheets
Technical proficiency regarding database design development, data
models, techniques for data mining, and segmentation
Experience in handling reporting packages like Business Objects, programming
( Javascript , XML, or ETL frameworks), databases
Knowledge of data visualization software like Tableau
Knowledge of how to create and apply the most accurate algorithms to datasets in
order to find solutions
Problem-solving skills
Accuracy and attention to detail
Adept at queries, writing reports, and making presentations
Team-working skills
Verbal and Written communication skills
Proven working experience in data analysis
Our client is an innovative Fintech company that is revolutionizing the business of short term finance. The company is an online lending startup that is driven by an app-enabled technology platform to solve the funding challenges of SMEs by offering quick-turnaround, paperless business loans without collateral. It counts over 2 million small businesses across 18 cities and towns as its customers.
- Performing extensive analysis on SQL, Google Analytics & Excel from a product standpoint to provide quick recommendations to the management
- Establishing scalable, efficient and automated processes to deploy data analytics on large data sets across platforms
What you need to have:
- B.Tech /B.E.; Any Graduation
- Strong background in statistical concepts & calculations to perform analysis/ modeling
- Proficient in SQL and other BI tools like Tableau, Power BI etc.
- Good knowledge of Google Analytics and any other web analytics platforms (preferred)
- Strong analytical and problem solving skills to analyze large quantum of datasets
- Ability to work independently and bring innovative solutions to the team
- Experience of working with a start-up or a product organization (preferred)
- Handling Survey Scripting Process through the use of survey software platform such as Toluna, QuestionPro, Decipher.
- Mining large & complex data sets using SQL, Hadoop, NoSQL or Spark.
- Delivering complex consumer data analysis through the use of software like R, Python, Excel and etc such as
- Working on Basic Statistical Analysis such as:T-Test &Correlation
- Performing more complex data analysis processes through Machine Learning technique such as:
- Classification
- Regression
- Clustering
- Text
- Analysis
- Neural Networking
- Creating an Interactive Dashboard Creation through the use of software like Tableau or any other software you are able to use.
- Working on Statistical and mathematical modelling, application of ML and AI algorithms
What you need to have:
- Bachelor or Master's degree in highly quantitative field (CS, machine learning, mathematics, statistics, economics) or equivalent experience.
- An opportunity for one, who is eager of proving his or her data analytical skills with one of the Biggest FMCG market player.
Job Description
We are looking for an experienced engineer to join our data science team, who will help us design, develop, and deploy machine learning models in production. You will develop robust models, prepare their deployment into production in a controlled manner, while providing appropriate means to monitor their performance and stability after deployment.
What You’ll Do will include (But not limited to):
- Preparing datasets needed to train and validate our machine learning models
- Anticipate and build solutions for problems that interrupt availability, performance, and stability in our systems, services, and products at scale.
- Defining and implementing metrics to evaluate the performance of the models, both for computing performance (such as CPU & memory usage) and for ML performance (such as precision, recall, and F1)
- Supporting the deployment of machine learning models on our infrastructure, including containerization, instrumentation, and versioning
- Supporting the whole lifecycle of our machine learning models, including gathering data for retraining, A/B testing, and redeployments
- Developing, testing, and evaluating tools for machine learning models deployment, monitoring, retraining.
- Working closely within a distributed team to analyze and apply innovative solutions over billions of documents
- Supporting solutions ranging from rule-bases, classical ML techniques to the latest deep learning systems.
- Partnering with cross-functional team members to bring large scale data engineering solutions to production
- Communicating your approach and results to a wider audience through presentations
Your Qualifications:
- Demonstrated success with machine learning in a SaaS or Cloud environment, with hands–on knowledge of model creation and deployments in production at scale
- Good knowledge of traditional machine learning methods and neural networks
- Experience with practical machine learning modeling, especially on time-series forecasting, analysis, and causal inference.
- Experience with data mining algorithms and statistical modeling techniques for anomaly detection in time series such as clustering, classification, ARIMA, and decision trees is preferred.
- Ability to implement data import, cleansing and transformation functions at scale
- Fluency in Docker, Kubernetes
- Working knowledge of relational and dimensional data models with appropriate visualization techniques such as PCA.
- Solid English skills to effectively communicate with other team members
Due to the nature of the role, it would be nice if you have also:
- Experience with large datasets and distributed computing, especially with the Google Cloud Platform
- Fluency in at least one deep learning framework: PyTorch, TensorFlow / Keras
- Experience with No–SQL and Graph databases
- Experience working in a Colab, Jupyter, or Python notebook environment
- Some experience with monitoring, analysis, and alerting tools like New Relic, Prometheus, and the ELK stack
- Knowledge of Java, Scala or Go-Lang programming languages
- Familiarity with KubeFlow
- Experience with transformers, for example the Hugging Face libraries
- Experience with OpenCV
About Egnyte
In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com
#LI-Remote
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.
- 6+ months of proven experience as a Data Scientist or Data Analyst
- Understanding of machine-learning and operations research
- Extensive knowledge of R, SQL and Excel
- Analytical mind and business acumen
- Strong Statistical understanding
- Problem-solving aptitude
- BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred
Data Analyst
at SveltetechTechnologies Pvt Ltd
Data Analyst Job Duties
Data analyst responsibilities include conducting full lifecycle analysis to include requirements, activities and design. Data analysts will develop analysis and reporting capabilities. They will also monitor performance and quality control plans to identify improvements.
Responsibilities
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Interpret data, analyze results using statistical techniques and provide ongoing reports
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Develop and implement databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality
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Acquire data from primary or secondary data sources and maintain databases/data systems
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Identify, analyze, and interpret trends or patterns in complex data sets
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Filter and “clean” data by reviewing computer reports, printouts, and performance indicators to locate and correct code problems
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Work with management to prioritize business and information needs
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Locate and define new process improvement opportunities
Requirements
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Proven working experience as a Data Analyst or Business Data Analyst
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Technical expertise regarding data models, database design development, data mining and segmentation techniques
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Strong knowledge of and experience with reporting packages (Business Objects etc), databases (SQL etc), programming (XML, Javascript, or ETL frameworks)
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Knowledge of statistics and experience using statistical packages for analyzing datasets (Excel, SPSS, SAS etc)
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Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
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Adept at queries, report writing and presenting findings
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BS in Mathematics, Economics, Computer Science, Information Management or Statistics
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NLP Engineer - Artificial Intelligence
at Artivatic.ai