Data Science Job Portal in India-finnstats is one of the job search portals for freshers. Irrespective of time or pandemic data science career is always a hot topic. Here are the latest data analysis job vacancy details.
If you are searching for data science jobs finnstats is one of the Data Science Job Portal in India
Find the details below, how top companies are hiring Data Experts basis different requirements.
1. Data Engineer
The Data Engineer will be responsible for:
- Working with the latest in open-source NoSQL technologies, primarily Apache Cassandra
- Implementing our large datasets using the latest in big data processing techniques
- Mentor a team of developers and infrastructure engineers on how to work with big data
- Building a Cassandra NoSQL datastore to report on all of our system and product data
- Migrating instances of data stores that do not fit the typical RDBMS model
- Work with stake holders to define problems, data collection, synthesize relevant data, build analytical models and forecasts
2. Data Scientist
The Data Scientist will:
- Understand product requirements and develop required AI/ML methods to address these requirements
- Extract data from different data sources using SQL, CQL etc.
- Process and clean the data using R programming
- Integrate and store data
- Perform data investigation and exploratory data analysis
- Choose one or more potential models and algorithms to address product requirements
- Apply data science techniques, such as Machine Learning, Statistical Modeling, and artificial intelligence
- Measure and Improve results
- Make adjustments based on feedback
3. Data Science Intern
- Undergrad in Engineering along with strong keen interest in statistics, data science.
- Experience in predictive modelling, data science and analysis
- Programming experience in Python or R.
- Experience making data presentations with graphical or data visualization tools
- Must have independently built or as part of a team effort built specific models from data sets achieving specific objective metrics.
- Should understand error metrics, hypothesis design, sampling and basic intuitive understanding of algorithms along with shortcomings/assumptions.
4. Research Intern
- Student must be enrolled in one of the following degree program: Btech/MS/Mtech/PhD
- Preferred degrees include Computer science, Mathematics.
- Student should have decent Linux programming exposure.
- Good to have some exposure to open source projects within Kubernetes/Big Data platform communities such as Knative, Operators, Fluentd, Prometheus, Elasticsearch etc.
- Good knowledge of software engineering practices including agile processes
- Student must have very strong problem-solving aptitude and ability to delve into multifaceted pieces of knowledge
5. Sr. Data Scientist
- Very good implementation and Understanding of AI/ML Techniques – Models, APIs, NLP, Deep Learning and Algorithm types. Familiarity of how to apply AI/ML in Industry use cases
- Experience with machine learning and AI and Familiarity with data management tools
- Experience with common data science toolkits
- Experience with big data technologies such as Hadoop and Spark
- Study and transform data science prototypes
- Research and implement appropriate ML algorithms and tools
- Deep knowledge of math, probability, statistics and algorithms
- Well-versed in Agile, other SDLC methodologies and can coordinate with owners and SMEs.
- Must have hands on experience in Python/R/Scala
- Experience in AI platform(s) that enable integrated data access exploration model management automation and data insights.
- Should have Excellent Communications Skills
- Should be a self-starter and must be able to adapt to changes
- Should be a quick learner interested in learning new technologies as per project needs.
- Understanding of telecom domain is preferable
- Should have worked as part of an agile development team (Lean / Pair / Agile programming)
- Prior experience of directly interfacing with customer is preferable, though not mandatory
- Should show high degree of ethics and be cautious with respect to various security stipulations
6. Data Engineer
- Analyze and organize raw data from multiple sources to produce requested or required data elements
- Build and maintain data systems and pipelines to support increases in data volume and complexity
- Create and maintain optimal data pipeline architecture
- Contribute towards the development, construction, and maintenance of data models within data warehouses using dimensional modeling
- Conduct complex data analysis and report on analysis to end-users using system tools and database or data warehouse queries and scripts
- Interpret trends and patterns
- Prepare data for prescriptive and predictive modeling
- Program and maintain reports, dashboards, data generators and other end-user information portals or resources
- Explore ways to enhance data quality and reliability
- Identify opportunities for data acquisition
- Develop analytical tools and programs to troubleshoot data related issues and assist in the resolution of data issues.
- Collaborate with analytics and business teams to improve data models in order to increase data accessibility and foster data driven decision making in the organization
- Manage complex projects with multiple team members
7. Risk Analyst
- Define KPIs to measure the efficiency of Digital Financial Product and consult engineering/OneAmex team on enabling digital activity tracking according to measurement framework
- Deliver strategic analysis focused on the product roadmap and provide actionable insights by mining digital activity along with Amex closed loop data
- Handle manipulation of large datasets on Hadoop / Cornerstone to ensure faster data analysis
- Explore & leverage different business intelligence tools like Tableau & custom tools to create and manage various business intelligence reports/dashboards for different product managers
- Deliver self-serve analytics focused on the product roadmap for GCS servicing digital products by gaining deep functional understanding of the GCS digital channels over time and ensure analytical insights are relevant and actionable
- Create, enhance and maintain data & reporting capabilities on big data environment that house various digital portfolio performance metrics focused on the product & marketing roadmap for Commercial Digital products
- Uplift the data visualization by creating meaningful and insightful reports using powerful visualization techniques and infographic tools.
- Build partnerships with Product and Marketing teams by working with them across product lifecycle
- Collaborate with the Product and Marketing team to generate insights on improving customer journeys and driving customer engagement to Digital Financial Product
- Conduct regular update sessions with key stakeholders on performance and improvement opportunities for Digital Financial Product
8. Data Visualization Analyst
- Develop and maintain automated reporting, dashboards, and other BI solutions using products such as Google Data Studio and other similar products
- Understands how to represent large sets of data and information in clear and concise visualizations
- Creates wireframes and visual examples to help define visualization needs
- Understands how to query, manipulate, merge and extract data from diverse data sources to be able to consolidate and synthesize information
- Use visualization to develop actionable insights and recommendations to deliver on the business objectives
- Manipulate data, flat files, and raw information into cohesive data sets for visualization using ETL tools
- Able to utilize APIs where readymade connectors are not available
- Maintain data governance and implement & recommend best practices in data management to ensure data accuracy
- Technical writing and PowerPoint presentation creation related to your projects