Akhil is available for hire
Hire AkhilAkhil Lohia
验证专家 in Engineering
数据分析开发人员
Location
印度卡纳塔克邦的班加罗尔
至今成员总数
2018年11月23日
Akhil is a data scientist and economist by training with experience across academia and corporate projects. He has modeled large volumes of customer clickstream data for end-to-end machine learning pipelines using Spark and Python as well as census, 问卷调查, 和随机对照试验数据. 他沟通非常好，并与跨时区的团队合作过. Akhil还擅长快速掌握新技能.
Portfolio
eka.care
Python，亚马逊网络服务，深度学习，机器学习...
MYRM科技有限责任公司
Pandas, Salesforce, 匹配系统, Jupyter笔记本, 亚马逊雅典娜...
MakeMyTrip
亚马逊SageMaker, PyTorch, 亚马逊网络服务(AWS)， PySpark, Data Science...
Experience
Availability
Full-time
首选的环境
Python, Git, PyCharm, Jupyter, Unix
最神奇的...
...project I've worked on was a customer support chatbot for the largest online travel agency in India.
工作经验
高级数据科学家
2020 - 2021
eka.care
- Developed a module that extracts relevant information from medical documents such as 处方, 病理实验室报告, and 疫苗接种证书 and makes them digitally available and searchable.
- Used LayoutLM model to exploit position and to extract the key terms in medical documents.
- 开发了从上传文档到实体提取的端到端管道, including document classification and manual data annotation steps on AWS ecosystem.
- Collaborated on designing medically relevant hierarchies for different medical conditions and symptoms using SNOMED CT, 这有助于医生在处方簿上提供情境选择.
技术:Python，亚马逊网络服务，深度学习，机器学习, Data Science, Amazon S3 (AWS S3), 亚马逊雅典娜, Jupyter笔记本, 数据分析, 需求分析
数据科学家
2020 - 2020
MYRM科技有限责任公司
- De-duplicated and cross-referenced customer records to be inserted from a disorganized collection of spreadsheets into the Salesforce system.
- 设计了一个数据库，用于将Salesforce数据迁移到基于RoR的系统.
- Led import from various sources into the Salesforce system for efficient tracking of leads and progression to different stages of deal completion.
Technologies: Pandas, Salesforce, 匹配系统, Jupyter笔记本, 亚马逊雅典娜, 数据分析
首席数据科学家
2017 - 2020
MakeMyTrip
- Developed a hotel-ranking model that used a user's recent interactions to show relevant results.
- Built a user intent prediction model based on a customer's activity in the eCommerce funnel.
- Constructed the NLP part of a chatbot for handling the post-sales requirements of the business.
- Collaborated on the design of a feature marketplace—a kind of data warehouse that combined data from several sources for use by data science models.
- Created a universal search for the travel domain which allowed users to search for hotels and flights using free text. This involved the application of NLP techniques to extract relevant fields from the text.
技术:亚马逊SageMaker, PyTorch, 亚马逊网络服务(AWS)， PySpark, Data Science, NumPy, Pandas, Apache气流, Redshift, Spark, 生成预训练变压器(GPT), GPT, 自然语言处理(NLP), 机器学习, Python, 人工智能(AI), Algorithms, 数据分析, Amazon S3 (AWS S3), NoSQL, 亚马逊雅典娜, Jupyter笔记本, Microsoft Power BI
数据科学家|分析师
2019 - 2019
Mix Tech(通过Toptal)
- Set up various dashboards over Redshift and Metabase to understand how the product was performing among different customer segments and devices.
- 分析客户数据并监控用户留存等统计数据, 应用安装/卸载率, 用户参与, 每日/每周/每月/季度表现, 以及客户在漏斗中的移动, etc.
- Developed a churn model using PySpark and Python which was used to target customers based on their probability of churn.
技术:亚马逊网络服务(AWS), 数据分析, Spark, 机器学习, Metabase, SQL, Redshift, Python, 数据分析, 数据建模, Amazon S3 (AWS S3), 亚马逊雅典娜, Jupyter笔记本, Microsoft Power BI
研究助理
2015 - 2017
庞培法布拉大学
- Developed a model linking household wealth to female infanticide in India through the marriage market.
- Estimated the structural model and conducted counterfactual policy simulations to inform interventions. Implementation using 亚马逊网络服务(AWS) for the heavy computational tasks.
- Developed theoretical solutions of the model with derivation of the equilibrium equations and checking the proofs. 在Matlab中对模型经济进行了仿真.
技术:Mathematica, MATLAB, Python，经济学，数据建模
Experience
数据科学特色市场
I developed a feature store in AWS Redshift that collates data from a number of different sources and makes them available in the desired format. 它使数据变得干净, 总是最新的, 并准备好用于生产中的机器学习模型.
数据标注工具
I improved an open-source data labeling tool in Django to create training data for an NLP classifier which was used in a chatbot. 它支持标记每个实例的动态选项.
Ranking
I developed a machine learning model to show personalized ranking to users based on their historical and recent interaction with products as well as similarity with other users.
南印度社区研究
I worked on research projects on the economics of social networks in South India involving a randomized control trial.
I developed and customized a name-matching algorithm to match incoming patients to the project’s census data.
I developed and customized a name-matching algorithm to match incoming patients to the project’s census data.
预测他们所有人
I developed an R-shiny-based machine learning application that predicts which Pokemon creature you would encounter at a given location and time in the Pokemon GO mobile game. 机器学习模型是在一个大型的公开游戏数据集上进行训练的.
实时多人游戏
I developed a real-time multiplayer game integrating Microsoft Kinect and Windows Phone that allows one player using the phone to generate obstacles for the player using the Kinect.
聊天机器人意图分类器
I made a deep learning based intent classification model for the chatbot of MakeMyTrip, 印度最大的在线旅行社. 这个意图分类器基于ULMFiT模型. 它能够在100多个类中对意图进行分类.
槽提取和意图分类
I developed a joint model based on sequence to sequence (Seq2Seq) architecture which allows a user to extract the intent and slot values from an utterance given to a chatbot.
医疗文件理解
A Python-based app for classifying and parsing medical documents (including lab reports, 处方, 疫苗接种证书, etc.).
这使得这些文件可以以数字方式获取和搜索. 这与Google Photos对杂乱无章的照片所做的非常相似. It makes all your medical documents organized in proper categories and easily searchable with the relevant medical terms, 即使是手写的.
这使得这些文件可以以数字方式获取和搜索. 这与Google Photos对杂乱无章的照片所做的非常相似. It makes all your medical documents organized in proper categories and easily searchable with the relevant medical terms, 即使是手写的.
Education
2016 - 2017
数据科学硕士学位
巴塞罗那经济研究生院-巴塞罗那，西班牙
2011 - 2015
经济学学士学位
印度理工学院坎普尔-坎普尔，印度
Skills
库/ api
Pandas, PySpark, NumPy, SpaCy, PyTorch, TensorFlow
Tools
Git, Jupyter, Redash, Apache气流, Amazon Elastic MapReduce (EMR), 亚马逊SageMaker, 亚马逊雅典娜, Microsoft Power BI, 亚马逊QuickSight, MATLAB, STATA, LaTeX, PyCharm, Mathematica
Frameworks
Spark, Django, Seq2Seq
Languages
Python, SQL, R, C, Java, Scala
Paradigms
数据科学，需求分析
Platforms
Linux, MacOS, 亚马逊网络服务(AWS), Jupyter笔记本, Docker, Unix, Salesforce
Storage
MySQL, Redshift, Apache Hive, Amazon S3 (AWS S3), Data Pipelines, Elasticsearch, NoSQL
Other
深度学习, Statistics, 预测学习, 预测建模, 数据可视化, 工程数据, Analytics, Big Data, Economics, 机器学习, 自然语言处理(NLP), 数据分析, 人工智能(AI), Algorithms, 数据分析, 机器学习操作(MLOps), GPT, 生成预训练变压器(GPT), 数据匹配, 统计建模, 库存管理系统, 推荐系统, 数据建模, Metabase, 自定义音频嵌入, 计算机视觉, 匹配系统
有效的合作
如何使用Toptal
Toptal matches you directly with global industry experts from our network in hours—not weeks or months.
1
分享你的需求
Discuss your requirements and refine your scope in a call with a Toptal domain expert.
2
选择你的才能
Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.
3
开始你的无风险人才试验
与你选择的人才一起工作，试用最多两周. 只有当你决定雇佣他们时才付钱.
对顶尖人才的需求很大.
Start hiring