is already being written. And if I spoke to your teachers, your friends, your professionals, your parents — I would know whether you’re trusted, how hard you work, whether you’re ethical – I would know so much about you. you would be shocked I don’t even have to meet you. So that book is already growing; you should write the book the way you want it to be written. You actually have that choice, and you can do it as you want now. ” — Jamie Dimon, CEO of JPMorgan Chase (Dimon, 2009)
Placement at Deloitte Financial Risk & Regulatory Team (FR&R) Intermediate data science skill set Jack Oliver blademaw.github.io Consulting firm; one of ‘big four’ Global presence; in over 150 countries Services “nearly 90% of Fortune Global 500 companies” Founded in 1845 Various Melbourne-based teams ("About Deloitte | Our global network of member firms", 2022)
me) Deloitte Touche Tohmatsu Limited Risk Advisory (RA) Audit & Assurance ... ... ... Regulatory & Legal Financial Risk & Regulatory (FR&R) Risk & Compliance • Provide clients with technical & analytical analyses relating to financial and legal matters • Focus on integration of technology within consulting; bridge between data science and finance • Teams aim to foster creativity and allow for space to innovate; experimentation is encouraged
life cycle are featured and can be assigned to undergraduates ◦ Data cleaning & transformation • Technology is used as a means of achieving a business outcome; undergraduates are free to experiment • Tasks require deep technical understanding and at least a fundamental business understanding Undergraduate (my title/role) Undergraduate /’Vacationer’ Graduate (Junior) Analyst … Partner … Context (of RA — FR&R) • Provide clients with technical & analytical analyses relating to financial and legal matters • Focus on integration of technology within consulting; bridge between data science and finance • Teams aim to foster creativity and allow for space to innovate; experimentation is encouraged
life cycle are featured and can be assigned to undergraduates ◦ Data cleaning & transformation • Technology is used as a means of achieving a business outcome; undergraduates are free to experiment • Tasks require deep technical understanding and at least a fundamental business understanding Undergraduate (my title/role) Undergraduate /’Vacationer’ Graduate (Junior) Analyst … Partner … Context (of RA — FR&R) • Provide clients with technical & analytical analyses relating to financial and legal matters • Focus on integration of technology within consulting; bridge between data science and finance • Teams aim to foster creativity and allow for space to innovate; experimentation is encouraged
life cycle are featured and can be assigned to undergraduates ◦ Data cleaning & transformation • Technology is used as a means of achieving a business outcome; undergraduates are free to experiment • Tasks require deep technical understanding and at least a fundamental business understanding Undergraduate (my title/role) Undergraduate /’Vacationer’ Graduate (Junior) Analyst … Partner … Context (of RA — FR&R) • Provide clients with technical & analytical analyses relating to financial and legal matters • Focus on integration of technology within consulting; bridge between data science and finance • Teams aim to foster creativity and allow for space to innovate; experimentation is encouraged
X992 POL-ID 1AQA92003 0004 E0020 BASE PREM = 2049.000 E0102 SPEC DISCOUNT = 0021.020 E0103 SPEC PREM = 2027.080 N221P SPEC LOY DISC = 0005.000- N221D SPEC LOY DISC AMT = 0101.354- N221A SPEC LOY PREM = 1925.726 INIT BONUS DISC *********** ERRORINSUM - NO BONUS DISC 1AQA92003 T0802 EXCESS PAYMENT = 0100.000- A0802 EXCESS PREM = 1825.726 MIN PREM = 1500.000 PREM AFT MIN PREM = 1825.726 * CouponDisc0023 Perc 25% Yr 1 * C0023 bf 1825.726 af 1369.295 * AgeBenefit3141 Amt 159 No Cap * AB3141 bf 1369.295 af 1210.295 FINAL PREM = 1500.000 ERRORINPOL - NO POL-ID 1AQA92003 0005 POLICY TRACE START ************************* … Problem/Input Client data only retrievable via semi-structured, parsed ‘tracing reports’ — need to convert to tabular format to conduct analysis. Client data will come in droves of gigabytes of text files; potentially millions of policies. Desired Solution Automated solution that accurately and efficiently captures data, exports to tabular format.
expressions (with re module) • Log files to track errors (via logging module) • DataFrame manipulation & exporting in pandas • String manipulation Technical • Experience with data cleaning and transformation • Ability to write complex regular expressions for feature engineering • Exposure to involved error handling and mechanisms to maintain audit trails • Increased knowledge of documentation and development best practices
via regular expressions (with re module) • Log files to track errors (via logging module) • DataFrame manipulation & exporting in pandas • String manipulation Technical • Experience with data cleaning and transformation • Ability to write complex regular expressions for feature engineering • Exposure to involved error handling and mechanisms to maintain audit trails • Increased knowledge of documentation and development best practices
representatives’ backgrounds (non-technical/technical) • Domain knowledge and awareness • Client relationships and etiquette • Absorbing new business information in real-time Work — case study (cont.) … … … … … … … Business Understanding
via regular expressions (with re module) • Log files to track errors (via logging module) • DataFrame manipulation & exporting in pandas • String manipulation Technical • Experience with data cleaning and transformation • Ability to write complex regular expressions for feature engineering • Exposure to involved error handling and mechanisms to maintain audit trails • Increased knowledge of documentation and development best practices
representatives’ backgrounds (non-technical/technical) • Domain knowledge and awareness • Client relationships and etiquette • Absorbing new business information in real-time Work — case study — skills (cont.) Technical ‘Soft’ • Ability to adopt and emulate energy of team or client representatives • Increased confidence in networking; client meetings • Ability to effectively communicate across contexts with relevant diction, tone • Ability to envision future development of work; account for prospective context • Pattern matching via regular expressions (with re module) • Log files to track errors (via logging module) • DataFrame manipulation & exporting in pandas • String manipulation • Experience with data cleaning and transformation • Ability to write complex regular expressions for feature engineering • Exposure to involved error handling and mechanisms to maintain audit trails • Increased knowledge of documentation and development best practices
representatives’ backgrounds (non-technical/technical) • Domain knowledge and awareness • Client relationships and etiquette • Absorbing new business information in real-time Work — case study — skills (cont.) Technical ‘Soft’ • Ability to adopt and emulate energy of team or client representatives • Increased confidence in networking; client meetings • Ability to effectively communicate across contexts with relevant diction, tone • Ability to envision future development of work; account for prospective context • Pattern matching via regular expressions (with re module) • Log files to track errors (via logging module) • DataFrame manipulation & exporting in pandas • String manipulation • Experience with data cleaning and transformation • Ability to write complex regular expressions for feature engineering • Exposure to involved error handling and mechanisms to maintain audit trails • Increased knowledge of documentation and development best practices
X992 POL-ID 1AQA92003 0004 E0020 BASE PREM = 2049.000 E0102 SPEC DISCOUNT = 0021.020 E0103 SPEC PREM = 2027.080 N221P SPEC LOY DISC = 0005.000- N221D SPEC LOY DISC AMT = 0101.354- N221A SPEC LOY PREM = 1925.726 INIT BONUS DISC *********** ERRORINSUM - NO BONUS DISC 1AQA92003 T0802 EXCESS PAYMENT = 0100.000- A0802 EXCESS PREM = 1825.726 MIN PREM = 1500.000 PREM AFT MIN PREM = 1825.726 * CouponDisc0023 Perc 25% Yr 1 * C0023 bf 1825.726 af 1369.295 * AgeBenefit3141 Amt 159 No Cap * AB3141 bf 1369.295 af 1210.295 FINAL PREM = 1500.000 ERRORINPOL - NO POL-ID 1AQA92003 0005 POLICY TRACE START ************************* … ‘Tasks’ in university (assignments) are often done in a bubble/vacuum Projects have a flow of work (‘pipelines’) • Work is almost always used in a long process that extends far beyond short-term tasks • Need to be aware of future use of work and output, and ideally account for future development in the short-term
RISK X992 POL-ID 1AQA92003 0004 E0020 BASE PREM = 2049.000 E0102 SPEC DISCOUNT = 0021.020 E0103 SPEC PREM = 2027.080 N221P SPEC LOY DISC = 0005.000- N221D SPEC LOY DISC AMT = 0101.354- N221A SPEC LOY PREM = 1925.726 INIT BONUS DISC *********** ERRORINSUM - NO BONUS DISC 1AQA92003 T0802 EXCESS PAYMENT = 0100.000- A0802 EXCESS PREM = 1825.726 MIN PREM = 1500.000 PREM AFT MIN PREM = 1825.726 * CouponDisc0023 Perc 25% Yr 1 * C0023 bf 1825.726 af 1369.295 * AgeBenefit3141 Amt 159 No Cap * AB3141 bf 1369.295 af 1210.295 FINAL PREM = 1500.000 ERRORINPOL - NO POL-ID 1AQA92003 0005 POLICY TRACE START ************************* … NOT something you would see in university! However, still a wholly natural problem… • Real-world clients often have messy situations with no perfectly-defined systems in place to handle them • No guarantee that documentation or experts will exist to be able to assist with technical/business understanding (limited ‘hand-holding’)
Limited • Must have a rudimentary understanding of financial matters, leveraging technical ability to pursue project business problems • Can adapt to work conditional on client’s agenda and requirements • Utilises technology to problem-solve across multiple teams and domains in accordance with client requirements • Aware of where (individual) work sits within bigger picture of project Financial Risk & Regulatory (FR&R) • Provide clients with technical & analytical analyses relating to financial and legal matters • Focus on integration of technology within consulting; bridge between data science and finance • Teams aim to foster creativity and allow for space to innovate; experimentation is encouraged }
to Deloitte 2. Develop a sense for effective workplace communication 3. Create meaningful connections and relationships to build a foundation of a professional network 4. Increase business acumen and strengthen technical skills 5. Employ time-management strategies and prioritisation to deal with client deadlines
to Deloitte 2. Develop a sense for effective workplace communication 3. Create meaningful connections and relationships to build a foundation of a professional network 4. Increase business acumen and strengthen technical skills 5. Employ time-management strategies and prioritisation to deal with client deadlines
to Deloitte 2. Develop a sense for effective workplace communication 3. Create meaningful connections and relationships to build a foundation of a professional network 4. Increase business acumen and strengthen technical skills 5. Employ time-management strategies and prioritisation to deal with client deadlines
Retrieved 1 June 2022, from https://www2.deloitte.com/global/en/pages/about-deloitte/articles/about-deloitte.html Dimon, J. (2009). Address to HBS MBA Class of 2009. Speech, Harvard Business School, https://www.youtube.com/watch?v=9T9Kp4NE5l4. Reference list Thank you for listening .
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