AWS Glue Developer

• Partners with business stakeholders to translate business objectives into clearly defined analytical projects.
• Identify opportunities for text analytics and NLP to enhance the core product platform, select the best machine learning techniques for the specific business problem and then build the models that solve the problem.
• Own the end-end process, from recognizing the problem to implementing the solution.
• Define the variables and their inter-relationships and extract the data from our data repositories, leveraging infrastructure including Cloud computing solutions and relational database environments.
• Build predictive models that are accurate and robust and that help our customers to utilize the core platform to the maximum extent.

• 12 to 15 yrs of experience.
• An advanced degree in predictive analytics, machine learning, artificial intelligence; or a degree in programming and significant experience with text analytics/NLP. He shall have a strong background in machine learning (unsupervised and supervised techniques). In particular, excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, logistic regression, MLPs, RNNs, etc.
• Experience with text mining, parsing, and classification using state-of-the-art techniques.
• Experience with information retrieval, Natural Language Processing, Natural Language
• Understanding and Neural Language Modeling.
• Ability to evaluate the quality of ML models and to define the right performance metrics for models in accordance with the requirements of the core platform.
• Experience in the Python data science ecosystem: Pandas, NumPy, SciPy, sci-kit-learn, NLTK, Gensim, etc.
• Excellent verbal and written communication skills, particularly possessing the ability to share technical results and recommendations to both technical and non-technical audiences.
• Ability to perform high-level work both independently and collaboratively as a project member or leader on multiple projects.

• Act as primary day-to-day contact on analytics to agency-client leads
• Develop bespoke analytics proposals for presentation to agencies & clients, for delivery within the teams
• Ensure delivery of projects and services across the analytics team meets our stakeholder requirements (time, quality, cost)
• Hands on platforms to perform data pre-processing that involves data transformation as well as data cleaning
  
• Ensure data quality and integrity
  
• Interpret and analyse data problems
  
• Build analytic systems and predictive models
  
• Increasing the performance and accuracy of machine learning algorithms through fine-tuning and further
  
• Visualize data and create reports
  
• Experiment with new models and techniques
  
• Align data projects with organizational goals

• Min 6 - 7 years’ experience working in Data Science
• Prior experience as a Data Scientist within a digital media is desirable
• Solid understanding of machine learning
• A degree in a quantitative field (e.g. economics, computer science, mathematics, statistics, engineering, physics, etc.)
• Experience with SQL/ Big Query/GMP tech stack / Clean rooms such as ADH
• A knack for statistical analysis and predictive modelling
• Good knowledge of R, Python
• Experience with SQL, MYSQL, PostgreSQL databases
• Knowledge of data management and visualization techniques
• Hands-on experience on BI/Visual Analytics Tools like PowerBI or Tableau or Data Studio
• Evidence of technical comfort and good understanding of internet functionality desirable
• Analytical pedigree - evidence of having approached problems from a mathematical perspective and working through to a solution in a logical way
• Proactive and results-oriented
• A positive, can-do attitude with a thirst to continually learn new things
• An ability to work independently and collaboratively with a wide range of teams
• Excellent communication skills, both written and oral

Title:- Data Scientist

Experience:-6 years

Work Mode:- Onsite

Primary Skills:- Data Science, SQL, Python, Data Modelling, Azure, AWS, Banking Domain (BFSI/NBFC)

Qualification:- Any

Roles & Responsibilities:-

1.  Acquiring, cleaning, and preprocessing raw data for analysis.

2.  Utilizing statistical methods and tools for analyzing and interpreting complex  datasets.

3.  Developing and implementing machine learning models for predictive analysis.

4.  Creating visualizations to effectively communicate insights to both technical and   non-technical stakeholders.

5.  Collaborating with cross-functional teams, including data engineers, business   analysts, and domain experts.

6.  Evaluating and optimizing the performance of machine learning models for   accuracy and efficiency.

7.  Identifying patterns and trends within data to inform business decision-making.

8.  Staying updated on the latest advancements in data science, machine learning, and  relevant technologies.

Requirement:- 

1.  Experience with modeling techniques such as Linear Regression, clustering, and classification techniques.

2.  Must have a passion for data, structured or unstructured.  0.6 – 5 years of hands-on experience with Python and SQL is a must.

3.   Should have sound experience in data mining, data analysis and machine learning techniques.

4.  Excellent critical thinking, verbal and written communications skills.

5.  Ability and desire to work in a proactive, highly engaging, high-pressure, client service environment.

6.   Good presentation skills.

Job Location: Hyderabad/Bangalore/ Chennai/Pune/Nagpur

Notice period: Immediate - 15 days

1.      Python Developer with Snowflake

Job Description :

1. 5.5+ years of Strong Python Development Experience with Snowflake.
2. Strong hands of experience with SQL ability to write complex queries.
3. Strong understanding of how to connect to Snowflake using Python, should be able to handle any type of files
4.  Development of Data Analysis, Data Processing engines using Python
5. Good Experience in Data Transformation using Python. 
6.  Experience in Snowflake data load using Python.
7.  Experience in creating user-defined functions in Snowflake.
8.  Snowsql implementation.
9.  Knowledge of query performance tuning will be added advantage.
10. Good understanding of Datawarehouse (DWH) concepts.
11.  Interpret/analyze business requirements & functional specification
12.  Good to have DBT, FiveTran, and AWS Knowledge.

Graas uses predictive AI to turbo-charge growth for eCommerce businesses. We are “Growth-as-a-Service”. Graas is a technology solution provider using predictive AI to turbo-charge growth for eCommerce businesses. Graas integrates traditional data silos and applies a machine-learning AI engine, acting as an in-house data scientist to predict trends and give real-time insights and actionable recommendations for brands. The platform can also turn insights into action by seamlessly executing these recommendations across marketplace store fronts, brand.coms, social and conversational commerce, performance marketing, inventory management, warehousing, and last mile logistics - all of which impacts a brand’s bottom line, driving profitable growth.

Roles & Responsibilities:

Work on implementation of real-time and batch data pipelines for disparate data sources.

• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies.
• Build and maintain an analytics layer that utilizes the underlying data to generate dashboards and provide actionable insights.
• Identify improvement areas in the current data system and implement optimizations.
• Work on specific areas of data governance including metadata management and data quality management.
• Participate in discussions with Product Management and Business stakeholders to understand functional requirements and interact with other cross-functional teams as needed to develop, test, and release features.
• Develop Proof-of-Concepts to validate new technology solutions or advancements.
• Work in an Agile Scrum team and help with planning, scoping and creation of technical solutions for the new product capabilities, through to continuous delivery to production.
• Work on building intelligent systems using various AI/ML algorithms. 

Desired Experience/Skill:

• Must have worked on Analytics Applications involving Data Lakes, Data Warehouses and Reporting Implementations.
• Experience with private and public cloud architectures with pros/cons.
• Ability to write robust code in Python and SQL for data processing. Experience in libraries such as Pandas is a must; knowledge of one of the frameworks such as Django or Flask is a plus.
• Experience in implementing data processing pipelines using AWS services: Kinesis, Lambda, Redshift/Snowflake, RDS.
• Knowledge of Kafka, Redis is preferred
• Experience on design and implementation of real-time and batch pipelines. Knowledge of Airflow is preferred.
• Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)

Roles & Responsibilities

• Designing and delivering a best-in-class, highly scalable data governance platform
• Improving processes and applying best practices
• Contribute in all scrum ceremonies; assuming the role of ‘scum master’ on a rotational basis
•  Development, management and operation of our infrastructure to ensure it is easy to deploy, scalable, secure and fault-tolerant
• Flexible on working hours as per business needs

We are a nascent quantitative hedge fund led by an MIT PhD and Math Olympiad medallist, offering opportunities to grow with us as we build out the team. Our fund has  world class investors and big data experts as part of the GP,  top-notch ML experts as advisers to the fund, plus has equity funding to grow the team, license data and scale the data processing.

We are interested in researching and taking in live a variety of quantitative strategies based on historic and live market data, alternative datasets, social media data (both audio and video) and stock fundamental data.

You would join, and, if qualified, lead a growing team of data scientists and researchers, and be responsible for a complete lifecycle of quantitative strategy implementation and trading.

Requirements:

• Atleast 3 years of relevant ML experience
• Graduation date : 2018 and earlier
•   3-5 years of experience in high level Python programming.
• Master Degree (or Phd) in quantitative disciplines such as Statistics, Mathematics, Physics, Computer Science in top universities.
•   Good knowledge of applied and theoretical statistics, linear algebra and machine learning techniques. 
•   Ability to leverage financial and statistical insights to research, explore and harness a large collection of quantitative strategies and financial datasets in order to build strong predictive models.
• Should take ownership for the research, design, development and implementation of the strategy development and effectively communicate with other team mates
•   Prior experience and good knowledge of lifecycle and pitfalls of algorithmic strategy development and modelling. 
•   Good practical knowledge in understanding financial statements, value investing, portfolio and risk management techniques.
•   A proven ability to lead and drive innovation to solve challenges and road blocks in project completion.
• A valid Github profile with some activity in it

Bonus to have:

•   Experience in storing and retrieving data from large and complex time series databases
•   Very good practical knowledge on time-series modelling and forecasting (ARIMA, ARCH and Stochastic modelling)
•   Prior experience in optimizing and back testing quantitative strategies, doing return and risk attribution, feature/factor evaluation. 
•   Knowledge of AWS/Cloud ecosystem is an added plus (EC2s, Lambda, EKS, Sagemaker etc.) 
•   Knowledge of REST APIs and data extracting and cleaning techniques 
•   Good to have experience in Pyspark or any other big data programming/parallel computing
•   Familiarity with derivatives, knowledge in multiple asset classes along with Equities.
•   Any progress towards CFA or FRM is a bonus
• Average tenure of atleast 1.5 years in a company