data scientist - (risk analyst) Jobs in Chennai

data scientist - (risk analyst)

junior data scientist - work from home Jobs in Chennai

junior data scientist - work from home

research scientist

data scientist

Tata Elxsi

<div>
 
 
 Purpose of the role:
 
 
 
 As a Data Scientist, the person will be responsible for bringing a combination of mathematical rigor and innovative algorithm design to create recipes that extract relevant insights from billions of rows of data to meaningfully improve user experience.
 
 
 
 
 
 
 KEY RESPONSIBILITIES:
 
 
 <ul>
 <li>
 Collect, clean, and preprocess structured and unstructured data from various sources.
 </li>
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 Develop and implement machine learning models and statistical algorithms.
 </li>
 <li>
 Perform exploratory data analysis to identify trends, patterns, and anomalies.
 </li>
 <li>
 Collaborate with cross-functional teams to understand business requirements and translate them into data solutions.
 </li>
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 Visualize data insights using tools like Tableau, Power BI, or matplotlib/seaborn.
 </li>
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 Communicate findings clearly to stakeholders through reports and presentations.
 </li>
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 Continuously improve data processes and model performance.
 </li>
 </ul>
 
 
 
 
 
 Experience:
 
 
 <ul>
 <li>
 Graduate degree or Phd in the following areas: Statistics, Data Science, Computer Science or relevant science or engineering discipline.
 </li>
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 Machine learning, data science skills with strong programming background in python.
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 5+ years of experience with common data science toolkits, such as scikit-learn, R, etc. Excellence in at least one of these is highly desirable.
 </li>
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 Great communication skills.
 </li>
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 Good Analytical skills
 </li>
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 Data-oriented personality
 </li>
 </ul>
 
 
 
 
 
 Skills &amp; Competencies:
 
 
 
 
 Must Have:
 
 
 <ul>
 <li>
 Python
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 scikit-learn, TensorFlow, or PyTorch.
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 Spark, Hadoop, Kafka,
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 AWS/ Azure/ Google Cloud
 </li>
 </ul>
 
 
 Good to Have
 
 
 <ul>
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 Spark (AWS EMR, Databricks), AWS Lambda
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 Spark Streaming and Batch
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 Avro, Parquet
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 Stream Data Platforms: AWS Kinesis
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 MySQL, Cassandra, HBase, MongoDB, RDBMS
 </li>
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 Caching Frameworks(ElasticCache/Redis)
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 Elasticsearch, Beats, Logstash, Kibana
 </li>
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 Java, Scala, Go, R
 </li>
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 Git, Maven, Gradle, Jenkins
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 Rancher, Puppet, Concourse, Docker, Ansible, Kubernetes
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 Linux
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 Presto, Athena
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 Keras, Pandas)
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 Visualization suite (AWS Quicksight, Grafana)
 </li>
 </ul>
</div>

Data Scientist

<div>
 
 Before you apply to a job, select your language preference from the options available at the top right of this page.
 
 
 
 Explore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrow&mdash;people with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level.
 
 
 
 Job Description
 
 
 
 
 DATA SCIENTIST
 
 
 
 
 Job Summary
 
 
 
 This
 
 Data Scientist
 
 creates and implements advanced analytics models and solutions to yield predictive and prescriptive insights from large volumes of structured and unstructured data. This position works with a team responsible for the research and implementation of predictive requirements by leveraging industry standard machine learning and data visualization tools to draw insights that empower confident decisions and product creation. This position leverages emerging tools and technologies available in On-prem and Cloud environments. This position utilizes industry standard machine learning and data visualization tools to transform data and analytics requirements into predictive solutions and provide data literacy on a range of machine learning systems at UPS. This position identifies opportunities for driving descriptive to predictive and prescriptive solutions, which become inputs to department and project teams on their decisions supporting projects.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Defines key data sources from UPS and external sources to deliver models.
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 Develops and implements pipelines that facilitates data cleansing, data transformations, data enrichments from multiple sources (internal and external) that serve as inputs for data and analytics systems.
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 For larger teams, works with data engineering teams to validate and test data and model pipelines identified during proof of concepts.
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 Develops data design based on the exploratory analysis of large amounts of data to discover trends and patterns that meet stated business needs.
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 Defines model key performance indicator (KPI) expectations and validation, testing, and re-training of existing models to meet business objectives.
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 Reviews and creates repeatable solutions through written project documentation, process flowcharts, logs, and commented clean code to produce datasets that can be used in analytics and/or predictive modeling.
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 Synthesizes insights and documents findings through clear and concise presentations and reports to stakeholders.
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 Presents operationalized analytic findings and provides recommendations.
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 Incorporates best practices on the use of statistical modeling, machine learning algorithms, distributed computing, cloud-based AI technologies, and run time performance tuning with the goal of deployment and market introduction.
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 Leverages emerging tools and technologies together with the use of open-source or vendor products in the creation and delivery of insights that support predictive and prescriptive solutions.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Expertise in R, SQL, Python and/or any other high-level languages.
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 Exploratory data analysis (EDA), data engineering and development of advanced analytics models.
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 Experience in development of AI and ML using platforms like VertexAI, Databricks or Sagemaker, and familiarity with available frameworks like PyTorch, Tensorflow and Keras.
 </li>
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 Experience applying models from small to medium scaled problems.
 </li>
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 Strong analytical skills and attention to detail.
 </li>
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 Able to engage key business and executive-level stakeholders to translate business problems to a high-level analytics solution approach.
 </li>
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 Expertise with statistical techniques, machine learning, and/or operations research and their application in business.
 </li>
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 Deep understanding of data management pipelines and experience in launching moderate scale advanced analytics projects in production.
 </li>
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 Demonstrated experience in Cloud-AI technologies and knowledge of environments both in Linux/Unix and Windows.
 </li>
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 Experience implementing open-source technologies and cloud services; with or without the use of enterprise data science platforms.
 </li>
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 Core AI / Machine Learning knowledge and application in supervised and unsupervised learning domains.
 </li>
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 Familiarity with Java or C++ is a plus.
 </li>
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 Solid oral and written communication skills, especially around analytical concepts and methods.
 </li>
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 Ability to communicate data through a story framework to convey data-driven results to technical and non-technical audiences.
 </li>
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 Master&rsquo;s Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience.
 
 
 </li>
 </ul>
 
 Last Day Posted - 2/25/2024
 
 
 
 
 Employee Type
 
 
 
 Permanent
 
 
 UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.
</div>

Infosys Finacle

<div>
 
 
 Role Designation:
 
 Senior Analyst - Data Science
 
 
 
 Job Location:
 
 Chennai
 
 
 
 
 <ul>
 <li>
 Minimum 4+years of Experience required.
 </li>
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 Excellent analytical and problem-solving skills .
 </li>
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 Experience using statistical computer languages (Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
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 Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
 </li>
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 Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks.
 </li>
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 Should be able to host the models and make them API convertible.
 </li>
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 Good communication and presentation skills to explain your work to people who don't understand the mechanics behind data analysis.
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 Working on Cutting Edge AI solutions in partnership with best of business in the industry. Propose innovate solutions and adopt quickly to dynamic learning environment.
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 Build AI algorithms and design experiments to merge, manage, interrogate, and extract data to supply tailored reports to colleagues, customers, or the wider organization .
 </li>
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 Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting, and other business outcomes. Bring about Explainable and Responsible AI.
 </li>
 <li>
 Conduct research from which you'll develop prototypes and proof of concepts Look for opportunities to use insights/datasets/code/models across other functions in the organization
 </li>
 <li>
 Stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work.
 </li>
 </ul>
</div>

Staples India

<div>
 
 Role Summary
 
 
 
 The Lead Data Engineer will strategically work in the data science team in applying advanced analytics, machine learning, LLMs and cutting-edge technologies to propose, perform and evaluate exploratory data analysis and predictive modelling to address critical ecommerce challenges. A creative and flexible approach to problem-finding should be combined with a strategical approach to maintaining the highest standards of data-driven decision-making with faithful application of development best practices.
 
 
 
 Duties &amp; Responsibilities
 
 :
 
 
 <ul>
 <li>
 
 Develop and deploy sophisticated machine learning and deep learning models to solve critical business challenges such as predict customer patterns, recommendation systems, demand forecasting, and predictive analytics.
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Leverage advanced techniques to extract insights, automate customer interactions, and enhance user experience across e-commerce platforms.
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Conduct thorough testing and validation of models, employing techniques such as cross-validation, A/B testing, and performance benchmarking to ensure models deliver accurate, reliable, and consistent results.
 
 
 </li>
 </ul>
 <ul>
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 Implement dynamic pricing strategies powered by reinforcement learning, Bayesian optimization, and price elasticity modeling, integrating real-time market intelligence and competitive data to optimize profitability and market share.
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Work closely with cross-functional teams to identify impactful business problems, and operationalize models using scalable deployment frameworks
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Stay informed of emerging trends and advancements in data science, machine learning operations, and AI ethics, continuously integrating new tools and techniques into the team's workflow.
 
 
 </li>
 <li>
 
 Ability to drive teams to success; ability to drive change and influence peers, leaders, collaborators, and individual contributors. Experience leading end-to-end data science project implementations working with Agile methodologies.
 
 
 </li>
 </ul>
 
 
 
 
 What you Bring to the Table:
 
 
 
 <ul>
 <li>
 
 Design, develop and implement business and technical features.
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Work with Architects to ensure the system is implemented as designed and in adherence with development guidelines and security standards.
 
 
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 </ul>
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 Partner with business, Product teams and other domain architects to translate business requirements and vision into core eCommerce functions.
 
 
 </li>
 </ul>
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 Create and evolve application documentation as required.
 
 
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 </ul>
 <ul>
 <li>
 
 Ensure that technical solutions follow best practices, are reliable and are easily maintainable
 
 
 </li>
 </ul>
 <li>
 </li>
 
 
 
 
 
 Years of Experience
 
 :
 
 
 
 Minimum of 6 years of experience with complex data science, applied statistics, machine learning, or mathematical modeling projects
 
 
 
 
 
 Requirements
 
 
 
 Basic Qualifications:
 
 
 
 <ul>
 <li>
 
 Bachelor&rsquo;s degree in in Analytics, Data Science, Statistics, Mathematics, Computer Science or a related field. Alternately equivalent experience in data analysis and predictive modeling will be considered in lieu of relevant degree.
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 6+ years of experience with complex data science, applied statistics, machine learning, or mathematical modeling projects.
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Hands on experience with deep learning frameworks, LLMs, GenAI tools, and applying NLP techniques.
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Expertise using tools like TensorFlow, PyTorch, LightGBM, XGBoost as well as general purpose programming languages such as GPT-4, BERT is preferred.
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Strong understanding of data and coding skills with SQL and Python.
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Excellent analytical abilities and a strong intellectual curiosity
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience with cloud platforms (e.g., Azure, AWS, GCP)
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proficient understanding of code versioning tools, such as Git / SVN
 
 
 </li>
 </ul>
 
 
 
 
 Preferred Qualifications:
 
 
 
 <ul>
 <li>
 
 Master&rsquo;s degree in computer science, Engineering, or a related field.
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience working in retail domains and developing e-commerce solutions.
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Familiarity with Agile methodologies and ability to thrive in fast-paced, collaborative environments.
 
 
 
 
 </li>
 </ul>
</div>

Mindsprint

<div>
 
 We are seeking an experienced
 
 Senior Data Science Engineer
 
 with 3+ years' experience
 
 
 to join our innovative team. As a Machine Learning and Generative AI Specialist, you will play a critical role in developing and deploying advanced ML models and algorithms to drive data-driven decision-making processes.
 
 
 
 
 
 Here are the key responsibilities and desired skills:
 
 
 
 
 
 
 1. Algorithm Development:
 
 
 
 o Design and implement machine learning algorithms for various applications, including natural language processing (NLP), recommendation systems, and predictive analytics.
 
 
 o Leverage your expertise in deep learning and generative AI to create innovative solutions.
 
 
 
 
 
 
 2. Data Processing and Analysis:
 
 
 
 o Collect, preprocess, and analyze large-scale datasets.
 
 
 o Apply statistical techniques and feature engineering to extract meaningful insights from data.
 
 
 
 
 
 
 3. Model Training and Evaluation:
 
 
 
 o Train and fine-tune ML models using Python and relevant libraries (e.g., TensorFlow, PyTorch).
 
 
 o Evaluate model performance using appropriate metrics and iterate to improve accuracy and efficiency.
 
 
 
 
 
 
 4. Deployment and Monitoring:
 
 
 
 o Deploy ML models to production environments (e.g., cloud platforms such as Azure, AWS, or GCP).
 
 
 o Monitor model performance, troubleshoot issues, and ensure robustness and reliability.
 
 
 
 
 
 
 5. Collaboration and Communication:
 
 
 
 o Collaborate with cross-functional teams, including data scientists, engineers, and product managers.
 
 
 o Communicate results and insights effectively to technical and non-technical stakeholders.
 
 
 
 
 
 
 Desired Skills:
 
 
 
 &bull; Machine Learning: Strong knowledge of
 
 ML algorithms,
 
 including supervised and unsupervised learning.
 
 
 &bull;
 
 Generative AI:
 
 Experience with generative models (e.g., GANs, VAEs) and their applications.
 
 
 &bull;
 
 Python:
 
 Proficiency in Python for data analysis, model development, and scripting.
 
 
 &bull;
 
 Cloud Platforms:
 
 Hands-on experience with Azure, AWS, or GCP for model deployment and scalability.
 
 
 &bull;
 
 Natural Language Processing (NLP)
 
 : Understanding of NLP techniques, sentiment analysis, and text generation.
 
 
 
</div>

ClinicMind

<div>
 ClinicMind is a leading healthcare SaaS platform that helps providers improve their practice financial performance, drive sustainable growth, and enhance patient care with integrated EHR, RCM, and Patient Engagement automation and excellent service solutions. outcomes, and maximizes revenue cycle efficiency.
 
 
 
 Position Summary
 
 
 
 The Junior Data Scientist will support the Data Science team in analyzing data, creating visual insights, and maintaining scalable data workflows using Amazon QuickSight and Amazon Redshift. This role is ideal for an entry-level candidate passionate about analytics, cloud data tools, and supporting data-driven business decisions.
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Data Management &amp; Preparation
 </li>
 <li>
 Extract, clean, and manage datasets within Amazon Redshift and related AWS data sources.
 </li>
 <li>
 Ensure data quality, consistency, and completeness for downstream analytics.
 </li>
 <li>
 Visualization &amp; Reporting
 </li>
 <li>
 Build and maintain Amazon QuickSight dashboards to communicate trends, KPIs, and actionable insights.
 </li>
 <li>
 Automate recurring reporting workflows and enhance dashboard interactivity.
 </li>
 <li>
 Data Analysis &amp; Insights
 </li>
 <li>
 Conduct exploratory data analysis (EDA) to uncover trends and patterns.
 </li>
 <li>
 Support business teams by generating ad-hoc analyses and presenting insights clearly.
 </li>
 <li>
 Collaboration &amp; Support
 </li>
 <li>
 Work closely with the Data Science Team Lead and cross-functional teams (Operations, Product, and Engineering).
 </li>
 <li>
 Participate in sprint reviews, data validation, and stakeholder discussions.
 </li>
 <li>
 Continuous Learning &amp; Innovation
 </li>
 <li>
 Stay up to date on AWS analytics services, BI tools, and data visualization best practices.
 </li>
 <li>
 Contribute new ideas for improving efficiency, visualization design, and automation.
 
 
 </li>
 </ul>
 
 Skills And Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Statistics, Mathematics, Data Analytics, or related field.
 </li>
 <li>
 Hands-on experience with Amazon QuickSight for dashboarding and reporting.
 </li>
 <li>
 Understanding of Amazon Redshift (queries, schemas, joins, and data pipelines).
 </li>
 <li>
 Knowledge of SQL for data extraction and transformation.
 </li>
 <li>
 Basic exposure to Python or R (optional but desirable).
 </li>
 <li>
 Strong analytical mindset and attention to detail.
 </li>
 <li>
 Good communication and presentation skills.
 
 
 </li>
 </ul>
 
 Preferred Certifications
 
 
 
 <ul>
 <li>
 AWS Certified Data Analytics
 </li>
 <li>
 Amazon QuickSight Author Certification
 </li>
 <li>
 AWS Cloud Practitioner or Practitioner Essentials
 
 
 </li>
 </ul>
 Must Have
 
 
 <ul>
 <li>
 Must have a stable internet connection minimum of 25 MBPS
 </li>
 <li>
 Must have a mobile data plan as a backup
 </li>
 <li>
 Must be in a quiet environment / work from home set-up
 </li>
 <li>
 Must be comfortable working the US Eastern Time business hours
 </li>
 <li>
 Minimum system requirement: Latest i5 with SSD hard disk (i7 preferred), 16 GB RAM (32 GB preferred)
 </li>
 </ul>
</div>

Junior Data Scientist - Work From Home

Weekday AI (YC W21)

<div>
 
 This role is for one of the Weekday's clients
 
 
 
 Min Experience: 6 years
 
 
 JobType: full-time
 
 
 This role is responsible for leading a team of 6-8 data analysts to deliver high-quality descriptive and diagnostic analytics across multiple product lines and business functions. The position involves generating timely insights, supporting analytical decision-making, and driving automation for recurring reporting and stakeholder requirements. It also plays a key part in strengthening risk models and enhancing analytical capabilities across the organization.
 
 
 
 Requirements
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 <ul>
 <li>
 Lead a team of data analysts to produce accurate MIS reports, variance analyses, and actionable insights within defined timelines.
 </li>
 <li>
 Conduct descriptive and diagnostic analytics across product portfolios and business verticals including acquisitions, cross-sell, customer service, and collections.
 </li>
 <li>
 Support stakeholders with data extraction, data manipulation, and operational analytics needs.
 </li>
 <li>
 Identify reporting gaps and recurring analytical requirements to automate dashboards in Tableau.
 </li>
 <li>
 Replicate and scale insights and reporting processes across different products and functions.
 </li>
 <li>
 Collaborate with business teams and modelling teams to provide analytical inputs that sharpen and improve ML model performance and usage.
 </li>
 <li>
 Drive the design, development, and deployment of ML/DL models supporting underwriting, portfolio management, and risk assessment.
 </li>
 <li>
 Monitor and enhance credit risk frameworks including Expected Credit Loss (ECL), vintage analysis, delinquency analysis, and other risk measurement methodologies.
 
 
 </li>
 </ul>
 
 Required Skills &amp; Qualifications
 
 
 
 <ul>
 <li>
 Experience: Minimum 8 years of experience in descriptive and diagnostic analytics within NBFC / BFSI or FinTech.
 </li>
 <li>
 Education: M.Tech / B.E / B.Tech / M.Sc in Computer Science, Statistics, Mathematics, or related field.
 </li>
 <li>
 Technical Expertise:
 </li>
 <ul>
 <li>
 Strong hands-on experience in SQL and Python.
 </li>
 <li>
 Proficiency in Tableau and Excel for dashboards, automation, and business insights.
 </li>
 <li>
 Experience with ML/DL model development and deployment.
 </li>
 </ul>
 <li>
 Risk Analytics Expertise:
 </li>
 <ul>
 <li>
 Credit risk modelling, portfolio monitoring, operational risk, and Expected Credit Loss (ECL).
 </li>
 <li>
 Time series forecasting, vintage and stress testing, simulations, and design of experiments.
 </li>
 <li>
 Delinquency analysis and On-Us / Off-Us analysis using credit bureau data.
 
 </li>
 </ul>
 </ul>
 
 
 Industry Exposure
 
 
 
 
 <ul>
 <li>
 BFSI (Banking, Financial Services &amp; Insurance)
 </li>
 <li>
 FinTech
 </li>
 </ul>
</div>

Data Scientist - (Risk Analyst)

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Junior Data Scientist - Work From Home

Data Scientist - (Risk Analyst)