Data Scientist

Job Title

Data Analyst

Job Brief

The successful candidate will turn data into information, information into insight and insight into business decisions.

Data Analyst Job Duties

Data analyst responsibilities include conducting full lifecycle analysis to include requirements, activities and design. Data analysts will develop analysis and reporting capabilities. They will also monitor performance and quality control plans to identify improvements.

Responsibilities

● Interpret data, analyze results using statistical techniques and provide ongoing reports.

● Develop and implement databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality.

● Acquire data fromprimary orsecondary data sources andmaintain databases/data systems.

● Identify, analyze, and interpret trends orpatternsin complex data sets.

● Filter and “clean” data by reviewing computerreports, printouts, and performance indicatorsto locate and correct code problems.

● Work withmanagementto prioritize business and information needs.

● Locate and define new processimprovement opportunities. 

Requirements

● Proven working experienceas aData Analyst or BusinessDataAnalyst.

● Technical expertise regarding data models, database design development, data mining and segmentation techniques.

● Strong knowledge of and experience with reporting packages (Business Objects etc), databases (SQL etc), programming (XML, Javascript, or ETL frameworks).

● Knowledge of statistics and experience using statistical packages for analyzing datasets (Excel, SPSS, SAS etc).

● Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.

● Adept atqueries,reportwriting and presenting findings.

Job Location SouthDelhi, New Delhi 

Key Roles/Responsibilities: –

• Develop an understanding of business obstacles, create

• solutions based on advanced analytics and draw implications for

• model development

• Combine, explore and draw insights from data. Often large and

• complex data assets from different parts of the business.

• Design and build explorative, predictive- or prescriptive

• models, utilizing optimization, simulation and machine learning

• techniques

• Prototype and pilot new solutions and be a part of the aim

• of ‘productifying’ those valuable solutions that can have impact at a

• global scale

• Guides and coaches other chapter colleagues to help solve

• data/technical problems at an operational level, and in

• methodologies to help improve development processes

• Identifies and interprets trends and patterns in complex data sets to

• enable the business to take data-driven decisions

  Strong knowledge in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, etc. 

 Sound Knowlegde querying databases and using statistical computer languages: R, Python, SQL, etc. 

 Strong understanding creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. 

About us

SteelEye is the only regulatory compliance technology and data analytics firm that offers transaction reporting, record keeping, trade reconstruction, best execution and data insight in one comprehensive solution. The firm’s scalable secure data storage platform offers encryption at rest and in flight and best-in-class analytics to help financial firms meet regulatory obligations and gain competitive advantage.

The company has a highly experienced management team and a strong board, who have decades of technology and management experience and worked in senior positions at many leading international financial businesses. We are a young company that shares a commitment to learning, being smart, working hard and being honest in all we do and striving to do that better each day. We value all our colleagues equally and everyone should feel able to speak up, propose an idea, point out a mistake and feel safe, happy and be themselves at work.

Being part of a start-up can be equally exciting as it is challenging. You will be part of the SteelEye team not just because of your talent but also because of your entrepreneurial flare which we thrive on at SteelEye. This means we want you to be curious, contribute, ask questions and share ideas. We encourage you to get involved in helping shape our business. What you'll do

What you will do?

• Deliver plugins for our python based ETL pipelines.
• Deliver python services for provisioning and managing cloud infrastructure.
• Design, Develop, Unit Test, and Support code in production.
• Deal with challenges associated with large volumes of data.
• Manage expectations with internal stakeholders and context switch between multiple deliverables as priorities change.
• Thrive in an environment that uses AWS and Elasticsearch extensively.
• Keep abreast of technology and contribute to the evolution of the product.
• Champion best practices and provide mentorship.

What we're looking for

• Python 3.
• Python libraries used for data (such as pandas, numpy).
• AWS.
• Elasticsearch.
• Performance tuning.
• Object Oriented Design and Modelling.
• Delivering complex software, ideally in a FinTech setting.
• CI/CD tools.
• Knowledge of design patterns.
• Sharp analytical and problem-solving skills.
• Strong sense of ownership.
• Demonstrable desire to learn and grow.
• Excellent written and oral communication skills.
• Mature collaboration and mentoring abilities.

What will you get?

• This is an individual contributor role. So, if you are someone who loves to code and solve complex problems and build amazing products and not worry about anything else, this is the role for you.
• You will have the chance to learn from the best in the business who have worked across the world and are technology geeks.
• Company that always appreciates ownership and initiative. If you are someone who is full of ideas, this role is for you.

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.

Skills:

- 5+ years deploying Machine Learning pipelines in large enterprise production systems.

- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.

Roles and Responsibilities:

Deploying ML models into production, and scaling them to serve millions of customers.

Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.

Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.

Provide software design and programming support to projects.

 Qualifications & Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.