Data Analyst

Description of Role: 

We are looking for a career-minded professional with global perspective to join the Mumbai based Data & Analytics Group (DAG).

Key responsibilities:

As part of the Data & Analytics Group (DAG) and reporting to the Head of the India DAG locally, the individual is responsible for the following –

1.Review, analyze, and resolve data quality issues for enterprise core data in the IM Data Warehouse.

2.Coordinate with data owners and other teams to identify root-cause of data quality issues and implement solutions.

3.Coordinate the onboarding of data from various internal / external sources into the central repository.

4.Work closely with Data Owners/Owner delegates on data analysis and development data quality (DQ) rules. Work with IT on enhancing DQ controls.

5.End-to-end analysis of business processes, data flows, and data usage to improve business productivity through re-engineering and data governance.

6.Interact with business stakeholders to identify, prioritize, and address data-related needs and issues.

7.Document business requirements and use cases for data-related projects.

8.Manage change control process and participate in user acceptance testing (UAT) activities.

9.Support other DAG initiatives.

Key Skills:

1.Ability to interact with business and technology teams to understand processes and data usage.

2.Ability to do data analysis - to trace data from source to consumption.

3.Capable of working across organization and as part of a cross-functional virtual team. Ability to work and think independently, but within a team-based approach.

4.Problem solver, self-starter, ability to work through an entire issue lifecycle. Ability to effectively prioritize and multi-task.

5.Strong communication skills

Key qualifications:

1.Bachelor’s Degree required and any other relevant academic course a plus.

2.Strong domain knowledge of investment data

3.5+ years of data management, data analytics, or data governance experience in financial services

4.Experience in data analysis, exploratory analysis using SQL and formulating data quality rules.

5.Experience working with BI reporting tools like Tableau, Power BI is preferred.

6.Knowledge in coding, Python is a plus.

7.Prior experience working with Data Platforms like Aladdin, FactSet, Bloomberg, MDM platforms preferred.

• 6+ years of data science experience.

• Demonstrated experience in leading programs.

• Prior experience in customer data platforms/finance domain is a plus.

• Demonstrated ability in developing and deploying data-driven products.

• Experience of working with large datasets and developing scalable algorithms.

• Hands-on experience of working with tech, product, and operation teams.

Technical Skills:

• Deep understanding and hands-on experience of Machine learning and Deep

learning algorithms. Good understanding of NLP and LLM concepts and fair

experience in developing NLU and NLG solutions.

• Experience with Keras/TensorFlow/PyTorch deep learning frameworks.

• Proficient in scripting languages (Python/Shell), SQL.

• Good knowledge of Statistics.

• Experience with big data, cloud, and MLOps.

Soft Skills:

• Strong analytical and problem-solving skills.

• Excellent presentation and communication skills.

• Ability to work independently and deal with ambiguity.

Continuous Learning:

• Stay up to date with emerging technologies.

Qualification.

A degree in Computer Science, Statistics, Applied Mathematics, Machine Learning, or any related field / B. Tech.

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

We are Still Hiring!!!

Dear Candidate,

This email is regarding open positions for Data Engineer Professionals with our organisation CRMNext.

In case, you find the company profile and JD matching your aspirations and your profile matches the required Skill and qualifications criteria, please share your updated resume with response to questions.

We shall reach you back for scheduling the interviews post this.

About Company:

Driven by a Passion for Excellence

Acidaes Solutions Pvt. Ltd. is a fast growing specialist Customer Relationship Management (CRM) product IT company providing ultra-scalable CRM solutions. It offers CRMNEXT, our flagship and award winning CRM platform to leading enterprises both on cloud as well as on-premise models. We consistently focus on using the state of art technology solutions to provide leading product capabilities to our customers.

CRMNEXT is a global cloud CRM solution provider credited with the world's largest installation ever. From Fortune 500 to start-ups, businesses across nine verticals have built profitable customer relationships via CRMNEXT. A pioneer of Digital CRM for some of the largest enterprises across Asia-Pacific, CRMNEXT's customers include global brands like Pfizer, HDFC Bank, ICICI Bank, Axis Bank, Tata AIA, Reliance, National Bank of Oman, Pavers England etc. It was recently lauded in the Gartner Magic Quadrant 2015 for Lead management, Sales Force Automation and Customer Engagement. For more information, visit us at www.crmnext.com

Educational Qualification:

B.E./B.Tech /M.E./ M.Tech/ MCA with (Bsc.IT/Bsc. Comp/BCA is mandatory)

60% in Xth, XIIth /diploma, B.E./B.Tech/M.E/M.Tech/ MCA with (Bsc.IT/Bsc. Comp/BCA is mandatory)

All education should be regular (Please Note - Degrees through Distance learning/correspondence will not consider)

Exp level- 2 to 5 yrs

Location-Andheri (Mumbai)

Technical expertise required:

1)Analytics experience in the BFSI domain is must

2) Hands on technical experience in python, big data and AI

3) Understanding of datamodels and analytical concepts

4) Client engagement :

Should have run in past client engagements for Big data/ AI projects starting from requirement gathering, to planning development sprints, and delivery

Should have experience in deploying big data and AI projects

First hand experience on data governance, data quality, customer data models, industry data models

Aware of SDLC.

Regards,
Deepak Sharma
HR Team

We are looking for a data scientist that will help us to discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products. 

• Selecting features, building and optimizing classifiers using machine learning techniques
• Data mining using state-of-the-art methods
• Extending company’s data with third party sources of information when needed
• Enhancing data collection procedures to include information that is relevant for building analytic systems
• Processing, cleansing, and verifying the integrity of data used for analysis
• Doing ad-hoc analysis and presenting results in a clear manner
• Creating automated anomaly detection systems and constant tracking of its performance

• Excellent understanding of machine learning techniques and algorithms, such as Linear regression, SVM, Decision Forests, LSTM, CNN etc.
• Experience with Deep Learning preferred.
• Experience with common data science toolkits, such as R, NumPy, MatLab, etc. Excellence in at least one of these is highly desirable
• Great communication skills
• Proficiency in using query languages such as SQL, Hive, Pig 
• Good applied statistics skills, such as statistical testing, regression, etc.
• Good scripting and programming skills 
• Data-oriented personality

Role and Responsibilities

• Execute data mining projects, training and deploying models over a typical duration of 2 -12 months.
• The ideal candidate should be able to innovate, analyze the customer requirement, develop a solution in the time box of the project plan, execute and deploy the solution.
• Integrate the data mining projects embedded data mining applications in the FogHorn platform (on Docker or Android).

Core Qualifications
Candidates must meet ALL of the following qualifications:

• Have analyzed, trained and deployed at least three data mining models in the past. If the candidate did not directly deploy their own models, they will have worked with others who have put their models into production. The models should have been validated as robust over at least an initial time period.
• Three years of industry work experience, developing data mining models which were deployed and used.
• Programming experience in Python is core using data mining related libraries like Scikit-Learn. Other relevant Python mining libraries include NumPy, SciPy and Pandas.
• Data mining algorithm experience in at least 3 algorithms across: prediction (statistical regression, neural nets, deep learning, decision trees, SVM, ensembles), clustering (k-means, DBSCAN or other) or Bayesian networks

Bonus Qualifications
Any of the following extra qualifications will make a candidate more competitive:

• Soft Skills
  • Sets expectations, develops project plans and meets expectations.
  • Experience adapting technical dialogue to the right level for the audience (i.e. executives) or specific jargon for a given vertical market and job function.
• Technical skills
  • Commonly, candidates have a MS or Ph.D. in Computer Science, Math, Statistics or an engineering technical discipline. BS candidates with experience are considered.
  • Have managed past models in production over their full life cycle until model replacement is needed. Have developed automated model refreshing on newer data. Have developed frameworks for model automation as a prototype for product.
  • Training or experience in Deep Learning, such as TensorFlow, Keras, convolutional neural networks (CNN) or Long Short Term Memory (LSTM) neural network architectures. If you don’t have deep learning experience, we will train you on the job.
  • Shrinking deep learning models, optimizing to speed up execution time of scoring or inference.
  • OpenCV or other image processing tools or libraries
  • Cloud computing: Google Cloud, Amazon AWS or Microsoft Azure. We have integration with Google Cloud and are working on other integrations.
  • Decision trees like XGBoost or Random Forests is helpful.
  • Complex Event Processing (CEP) or other streaming data as a data source for data mining analysis
  • Time series algorithms from ARIMA to LSTM to Digital Signal Processing (DSP).
  • Bayesian Networks (BN), a.k.a. Bayesian Belief Networks (BBN) or Graphical Belief Networks (GBN)
  • Experience with PMML is of interest (see www.DMG.org).
• Vertical experience in Industrial Internet of Things (IoT) applications:
  • Energy: Oil and Gas, Wind Turbines
  • Manufacturing: Motors, chemical processes, tools, automotive
  • Smart Cities: Elevators, cameras on population or cars, power grid
  • Transportation: Cars, truck fleets, trains

About FogHorn Systems
FogHorn is a leading developer of “edge intelligence” software for industrial and commercial IoT application solutions. FogHorn’s Lightning software platform brings the power of advanced analytics and machine learning to the on-premise edge environment enabling a new class of applications for advanced monitoring and diagnostics, machine performance optimization, proactive maintenance and operational intelligence use cases. FogHorn’s technology is ideally suited for OEMs, systems integrators and end customers in manufacturing, power and water, oil and gas, renewable energy, mining, transportation, healthcare, retail, as well as Smart Grid, Smart City, Smart Building and connected vehicle applications.

Press:  https://www.foghorn.io/press-room/">https://www.foghorn.io/press-room/

Awards: https://www.foghorn.io/awards-and-recognition/">https://www.foghorn.io/awards-and-recognition/

• 2019 Edge Computing Company of the Year – Compass Intelligence
• 2019 Internet of Things 50: 10 Coolest Industrial IoT Companies – CRN
• 2018 IoT Planforms Leadership Award & Edge Computing Excellence – IoT Evolution World Magazine
• 2018 10 Hot IoT Startups to Watch – Network World. (Gartner estimated 20 billion connected things in use worldwide by 2020)
• 2018 Winner in Artificial Intelligence and Machine Learning – Globe Awards
• 2018 Ten Edge Computing Vendors to Watch – ZDNet & 451 Research
• 2018 The 10 Most Innovative AI Solution Providers – Insights Success
• 2018 The AI 100 – CB Insights
• 2017 Cool Vendor in IoT Edge Computing – Gartner
• 2017 20 Most Promising AI Service Providers – CIO Review

Our Series A round was for $15 million.  Our Series B round was for $30 million October 2017.  Investors include: Saudi Aramco Energy Ventures, Intel Capital, GE, Dell, Bosch, Honeywell and The Hive.

About the Data Science Solutions team
In 2018, our Data Science Solutions team grew from 4 to 9.  We are growing again from 11. We work on revenue generating projects for clients, such as predictive maintenance, time to failure, manufacturing defects.  About half of our projects have been related to vision recognition or deep learning. We are not only working on consulting projects but developing vertical solution applications that run on our Lightning platform, with embedded data mining.

Our data scientists like our team because:

• We care about “best practices”
• Have a direct impact on the company’s revenue
• Give or receive mentoring as part of the collaborative process
• Questions and challenging the status quo with data is safe
• Intellectual curiosity balanced with humility
• Present papers or projects in our “Thought Leadership” meeting series, to support continuous learning