24+ Statistical Modeling Jobs in India

Data Science:

• Python expert level, Analytical, Different models works, Basic concepts, CPG(Domain).

• Statistical Models & Hypothesis , Testing

• Machine Learning Important

• Business Understanding, visualization in Python.

• Classification, clustering and regression

•

Mandatory Skills

• Data Science, Python, Machine Learning, Statistical Models, Classification, clustering and regression

Responsibilities

This role requires a person to support business charters & accompanying products by aligning with the Analytics

Manager’s vision, understanding tactical requirements and helping in successful execution. Split would be approx.

70% management + 30% individual contributor. Responsibilities include

Project Management

- Understand business needs and objectives.

- Refine use cases and plan iterations and deliverables - able to pivot as required.

- Estimate efforts and conduct regular task updates to ensure timeline adherence.

- Set and manage stakeholder expectations as required

Quality Execution

- Help BA and SBA resources with requirement gathering and final presentations.

- Resolve blockers regarding technical challenges and decision-making.

- Check final deliverables for correctness and review codes, along with Manager.

KPIs and metrics

- Orchestrate metrics building, maintenance, and performance monitoring.

- Owns and manages data models, data sources, and data definition repo.

- Makes low-level design choices during execution.

Team Nurturing

- Help Analytics Manager during regular one-on-ones + check-ins + recruitment.

- Provide technical guidance whenever required.

- Improve benchmarking and decision-making skills at execution-level.

- Train and get new resources up-to-speed.

- Knowledge building (methodologies) to better position the team for complex problems.

Communication

- Upstream to document and discuss execution challenges, process inefficiencies, and feedback loops.

- Downstream and parallel for context-building, mentoring, stakeholder management.

Analytics Stack

- Analytics : Python / R + SQL + Excel / PPT, Colab notebooks

- Database : PostgreSQL, Amazon Redshift, DynamoDB, Aerospike

- Warehouse : Amazon Redshift

- ETL : Lots of Python + custom-made

- Business Intelligence / Visualization : Metabase + Python/R libraries (location data)

- Deployment pipeline : Docker, Git, Jenkins, AWS Lambda

Role : Senior Customer Scientist 

Experience : 6-8 Years 

Location : Chennai (Hybrid) 
 
 

Who are we? 
 
 

A young, fast-growing AI and big data company, with an ambitious vision to simplify the world’s choices. Our clients are top-tier enterprises in the banking, e-commerce and travel spaces. They use our core AI-based choice engine http://maya.ai/">maya.ai, to deliver personal digital experiences centered around taste. The http://maya.ai/">maya.ai platform now touches over 125M customers globally. You’ll find Crayon Boxes in Chennai and Singapore. But you’ll find Crayons in every corner of the world. Especially where our client projects are – UAE, India, SE Asia and pretty soon the US. 
 
 

Life in the Crayon Box is a little chaotic, largely dynamic and keeps us on our toes! Crayons are a diverse and passionate bunch. Challenges excite us. Our mission drives us. And good food, caffeine (for the most part) and youthful energy fuel us. Over the last year alone, Crayon has seen a growth rate of 3x, and we believe this is just the start. 
 

 
We’re looking for young and young-at-heart professionals with a relentless drive to help Crayon double its growth. Leaders, doers, innovators, dreamers, implementers and eccentric visionaries, we have a place for you all. 
 

Can you say “Yes, I have!” to the below? 
 
 

1. Experience with exploratory analysis, statistical analysis, and model development 
    

1. Knowledge of advanced analytics techniques, including Predictive Modelling (Logistic regression), segmentation, forecasting, data mining, and optimizations 
    

1. Knowledge of software packages such as SAS, R, Rapidminer for analytical modelling and data management. 
    

1. Strong experience in SQL/ Python/R working efficiently at scale with large data sets 
    

1. Experience in using Business Intelligence tools such as PowerBI, Tableau, Metabase for business applications 
    

Can you say “Yes, I will!” to the below? 
 
 

1. Drive clarity and solve ambiguous, challenging business problems using data-driven approaches. Propose and own data analysis (including modelling, coding, analytics) to drive business insight and facilitate decisions. 
    

1. Develop creative solutions and build prototypes to business problems using algorithms based on machine learning, statistics, and optimisation, and work with engineering to deploy those algorithms and create impact in production. 
    

1. Perform time-series analyses, hypothesis testing, and causal analyses to statistically assess the relative impact and extract trends 
    

1. Coordinate individual teams to fulfil client requirements and manage deliverable 
    

1. Communicate and present complex concepts to business audiences 
    

1. Travel to client locations when necessary  

Crayon is an equal opportunity employer. Employment is based on a person's merit and qualifications and professional competences. Crayon does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, marital status, pregnancy or related.  
 
 

More about Crayon: https://www.crayondata.com/">https://www.crayondata.com/  
 

More about http://maya.ai/">maya.ai: https://maya.ai/">https://maya.ai/  

Your Day-to-Day

• Assist our Growth Strategists in analyzing the results of A/B experiments.
• Analysis on customer engagement rates, customer acquisition projects ( ex. Churn rate prediction, Attribution etc. )
• Analyse marketing channel performance and Deep-dive reports to stakeholders and Management
• Building statistical experimentation templates for faster A/B outputs
• Work on forecasting models and assisting senior Management in creating frameworks on growth models

• Local implementation of marketing analytics projects related to improving marketing channels effectiveness, customer segmentation, campaign optimization, etc
• Monitor campaigns against key performance indicators (KPIs), be fully aware of trends and analytics, success and risks in order to achieve business objectives.

• Communicate complex ideas into understandable reports/documentation and this will include leveraging on leading software tools such as Tableau.
  
  

Your Know-Know

• 3-5 years of experience in strategy / consulting / analytical / project management roles; experience in e-commerce, Start-ups or Unicorns(CARS24,OLA,SWIGGY,FLIPKART,OYO) or entrepreneur experience preferred + At Least 2 years of experience leading a team
• Top-notch academics from a Tier 1 college (IIM / IIT/ NIT)
• Must have SQL/PostgreSQL/Tableau Experience. 
• Added advantage: Experience with Google Analytics, CRM (MoEngage, Braze,Leanplum).
• Preferred knowledge of statistical computer languages (Python / R, etc). 
• Analytical mindset with ability to present data in a structured and informative way
• Enjoy a fast-paced environment and can align business objectives with product priorities

The role of a Personal Loan Risk Head is to own, manage and communicate risk policies and processes. He/She shall provide hands-on development of risk models involving market, credit and operational risk, assure controls are operating effectively, and provide research and analytical support. Prospective candidates must have excellent quantitative and analytical skills, along with the ability to apply those skills across a variety of business processes.

Key Expectations

• Designing and implementing an overall risk management process for the Personal Loan portfolio, which includes an analysis of the financial impact on the company when risks occur
• Performing a risk assessment: Analyzing current risks and identifying potential risks that are affecting the company
• Own the portfolio risk metrics - Loss forecasting, Stress testing, Credit Risk, Liquidity risk, Collections performance & strategy & overall ROA by segment.
• Monitor portfolio risk from granular dimensions and constantly implement strategies to maintain risk metrics within specific ranges.
• Monitor various operational metrics and develop alerting mechanisms to maintain process efficiency
• Designing and implementing strategies for Underwriting, Account Management, Portfolio Monitoring and Collections
• Develop risk based credit policies and pricing grids to maximize approvals within specific segments of risk
• Work with data science team which will develop algorithms and scorecards and drive decision models across various business segments.
• Partner with Engineering team to implement policies and scorecards.
• Supervise creation of time-sensitive analytics, visualisations, and complicated, high-visibility reports for Risk and Business management to use in portfolio monitoring and strategic decision-making.

Competencies -

• Have strong business understanding of the retail lending business in India and understanding of the regulatory landscape
• Should have hands-on experience working as data analyst or data scientist or statistical modeler in retail space, preferably in financial services or ecommerce.
• Strong experience in establishing and managing high-performing teams with a collaborative leadership approach.
• Outstanding communication skills, both verbal and written          

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.

 http://www.altimetrik.com/">http://www.altimetrik.com

https://www.youtube.com/watch?v=3nUs4YxppNE&;feature=emb_rel_end">https://www.youtube.com/watch?v=3nUs4YxppNE&;feature=emb_rel_end

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• Building out and manage a young data science vertical within the organization

• Provide technical leadership in the areas of machine learning, analytics, and data sciences

• Work with the team and create a roadmap to solve the company’s requirements by solving data-mining, analytics, and ML problems by Identifying business problems that could be solved using Data Science and scoping it out end to end.

• Solve business problems by applying advanced Machine Learning algorithms and complex statistical models on large volumes of data.

• Develop heuristics, algorithms, and models to deanonymize entities on public blockchains

• Data Mining - Extend the organization’s proprietary dataset by introducing new data collection methods and by identifying new data sources.

• Keep track of the latest trends in cryptocurrency usage on open-web and dark-web and develop counter-measures to defeat concealment techniques used by criminal actors.

• Develop in-house algorithms to generate risk scores for blockchain transactions.

• Work with data engineers to implement the results of your work.

• Assemble large, complex data sets that meet functional / non-functional business requirements.

• Build, scale and deploy holistic data science products after successful prototyping.

• Clearly articulate and present recommendations to business partners, and influence future plans based on insights.

• >8+ years of relevant experience as a Data Scientist or Analyst. A few years of work experience solving NLP problems or other ML problems is a plus

• Must have previously managed a team of at least 5 data scientists or analysts or demonstrate that they have prior experience in scaling a data science function from the ground 

• Good understanding of python, bash scripting, and basic cloud platform skills (on GCP or AWS)

• Excellent communication skills and analytical skills

• Work closely with the Founders in helping grow the organization to the next level alongside some of the best and brightest talents around you

• An excellent culture, we encourage collaboration, growth, and learning amongst the team

• Competitive salary and equity

• An autonomous and flexible role where you will be trusted with key tasks.

• An opportunity to have a real impact and be part of a company with purpose.

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

• 3+ years experience in practical implementation and deployment of ML based systems preferred.
• BE/B Tech or M Tech (preferred) in CS/Engineering with strong mathematical/statistical background
• Strong mathematical and analytical skills, especially statistical and ML techniques, with familiarity with different supervised and unsupervised learning algorithms
• Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimisation
• Experience in working on modeling graph structures related to spatiotemporal systems
• Programming skills in Python
• Experience in developing and deploying on cloud (AWS or Google or Azure)
• Good verbal and written communication skills
• Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow

• 3+ years’ experience developing and implementing enterprise-scale reports and dashboards.

• Proficiency with MS Power BI / SSRS.

• Knowledge of logical and physical data modeling concepts (relational and dimensional).

• Understanding of structured query language (SQL).

The person holding this position is responsible for leading the solution development and implementing advanced analytical approaches across a variety of industries in the supply chain domain.

At this position you act as an interface between the delivery team and the supply chain team, effectively understanding the client business and supply chain.

Candidates will be expected to lead projects across several areas such as

• Demand forecasting
• Inventory management
• Simulation & Mathematical optimization models.
• Procurement analytics
• Distribution/Logistics planning
• Network planning and optimization

Qualification and Experience

• 4+ years of analytics experience in supply chain – preferable industries hi-tech, consumer technology, CPG, automobile, retail or e-commerce supply chain.
• Master in Statistics/Economics or MBA or M. Sc./M. Tech with Operations Research/Industrial Engineering/Supply Chain
• Hands-on experience in delivery of projects using statistical modelling

Skills / Knowledge

• Hands on experience in statistical modelling software such as R/ Python and SQL.
• Experience in advanced analytics / Statistical techniques – Regression, Decision tress, Ensemble machine learning algorithms etc. will be considered as an added advantage.
• Highly proficient with Excel, PowerPoint and Word applications.
• APICS-CSCP or PMP certification will be added advantage
• Strong knowledge of supply chain management
• Working knowledge on the linear/nonlinear optimization
• Ability to structure problems through a data driven decision-making process.
• Excellent project management skills, including time and risk management and project structuring.
• Ability to identify and draw on leading-edge analytical tools and techniques to develop creative approaches and new insights to business issues through data analysis.
• Ability to liaison effectively with multiple stakeholders and functional disciplines.
• Experience in Optimization tools like Cplex, ILOG, GAMS will be an added advantage.

We are looking for someone with 6+ years of relevant experience working on problems in NLP or Computer Vision with a Master's degree (PhD preferred).