5 New job openings for Data Scientists in India
Data Science and Analytics are the biggest job creators amid the Covid-19 pandemic. Global tech firms continue to hire skilled techies for Data Science related job roles. Here are the 5 latest job openings with top companies that are hiring data scientists.
1. Data Scientist at Yoodle | Bengaluru
- Work independently or in team to solve complex problems and create scalable models/algorithms that will be integrated into Yoodle’s tools and products.
- Come up with actionable ideas to solve problems faced by product managers senior leadership then implement those ideas .
- Communicate context, data, solution and implications to the team, senior leaders and stakeholders.
- Lead and guide junior data scientists to deliver results (if applicable)
- Collaborate with other teams like quality assurance team and engineer team (if applicable)
- Candidates should have demonstrated the use of Data Science to solve real world problems with large data sets.
- Hands on experience in one of the relevant field viz. Data Science, Machine Learning, Deep Learning.
- Ability to write code and perform following tasks using at least one of Python (preferred), R, Matlab.
- Data processing / analysis / manipulation
- Predictive modeling
- Data processing / analysis / manipulation
- Conceptual understanding of some statistical modelling/machine learning algorithms.
- Able to handle large datasets
2. Machine Learning Engineer at Byju’s | Bengaluru
- Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
- Managing available resources such as hardware, data, and personnel so that deadlines are met
- Analysing the ML algorithms that could be used to solve a given problem and ranking them by their success probability
- Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
- Verifying data quality, and/or ensuring it via data cleaning
- Supervising the data acquisition process if more data is needed
- Finding available data sets online that could be used for training
- Defining validation strategies Defining the pre-processing or feature engineering to be done on a given data set
- Defining data augmentation pipelines
- Training models and tuning their hyper parameters
- Analysing the errors of the model and designing strategies to overcome them – Deploying models to production
- Proficiency with a deep learning framework such as Tensor Flow or Keras
- Proficiency with Python and basic libraries for machine learning such as sci kit-learn and pandas
- Expertise in visualizing and manipulating big data sets
- Proficiency with Open CV
- Familiarity with Linux
- Ability to select hardware to run an ML model with the required latency
3. Machine Learning Engineer at Hitachi Vantara | Bengaluru
- Perform machine learning, text analytics, and statistical analysis methods, such as classification, collaborative filtering, association rules, sentiment analysis, topic modeling, time-series analysis, regression, statistical inference, and validation methods.
- Selecting features, building and optimizing classifiers using machine learning techniques.
- Implement algorithms and software needed to perform analyses.
- Communicate results and educate others through reports and presentations.
- Expertise in Data Mining, Data wrangling, and data munging using one or more of the most commonly used data science tools: R, Python, SAS, SPSS, Weka â€¢ Experience in end-to-end data science and engineering activities.
4. Data Analyst at Shaadi.com | Mumbai
- Expertise in deriving insights from large amounts of data is mandatory
- Expertise in customer segmentation, user profiling, churn analysis is required
- Ability to work with large data sets and to interpret them statistically is expected
- Strong problem solving skills is required
- Ability to work with data warehousing solutions to meet large datasets and analysis requirements is expected
- Experience in working with visualization platforms such as Tableau, Looker, Qlik etc will be useful
- Experience using machine learning algorithms, data analytics strong algorithmic thinking and good programming skills will be useful
- Expertise with SQL and MS Excel is mandatory
- Detailed understanding of statistical techniques is expected
- Proficiency in R or Python will be useful.
- Ability to understand and explain issues from both a technical and a business point of view is useful
- Knowledge of various analytics techniques will be expected
- Experience working on analytics and tracking tools such as Google Analytics will be preferred
5. Applied AI & Machine Learning – Analyst at JPMorgan & Chase | Hyderabad
- Collaborate with Research teams to formulate relevant financial and business questions that can be answered by data analysis.
- Leverage your strong analytical background in order to collaborate with various business partners to:
- Work in a team responsible for generating information extraction and interpretation utilities and related workflows, strategy and automation initiatives (for instance writing scripts, web scraping, calling APIs, write SQL queries, python scripting etc.).
- Develop business and technical requirement documents; design and develop automated workflows; deploy workflows for automation, as well as use Third Party Data in workflows.
- Accountable for understanding business stakeholder’s data requirements; data interfaces and data mappings; analyze and interpret data.
- Design and implement automation policies to help our customers be more productive.
- Communicate final results and give context and document approach and techniques used.
- Collaborate with JP Morgan machine learning teams.
- Bachelor’s Degree in engineering, preferably in computer science or information technology.
- 1-3 years of experience across Data Analysis, Data Engineering, Automation, and Webscraping.
- Experience in integrating vendor products to a local ecosystem, and relevant infrastructure know how (taking a vendor product from POC to deployment in multiple environments).
- Expertise in sourcing, manipulating large and complex datasets, and Python scraping frameworks.
- Expertise in developing and debugging in Python or similar professional programming language.
- Strong collaboration, and communication skills.
- Results driven individual with high-level of curiosity and ability to dive into details without losing sight of the big picture.
- Exceptional organization skills to prioritize, manage, and implement a variety of competing initiatives, on a concurrent or staggered basis.